diff --git a/docs/faq.md b/docs/faq.md index f2abc7f0c..af0e74584 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -258,6 +258,17 @@ OpenCL / Vulkan 采用静态变量自注册的方式往 MNN 主库注册后端. ### Register 相关内存泄露说明 用 valgrind 工具检查时会报 MNN Register 相关的内存泄露，这个属于一次性的初始化内存，后续也不会增加，可视为误报 +### Metal 相关内存增长说明 + +Metal 后端使用的是OC对象，需要用OC的自动回收机制来清除内存，可在使用代码中把相关mnn的API调用放到autorealse中以自动回收内存 + +``` +@autoreleasepool { + /* MNN 相关调用代码 */ +} + +``` + ## 性能相关 ### 使用 GPU 时，调用 copyToHostTensor / readMap 非常慢 diff --git a/docs/tools/compress.md b/docs/tools/compress.md index b98a0371a..b80386a23 100644 --- a/docs/tools/compress.md +++ b/docs/tools/compress.md @@ -28,7 +28,7 @@ MNN模型压缩工具提供了包括低秩分解、剪枝、量化等模型压 | 训练量化 | 将float卷积转换为int8卷积计算，需要进行训练，可提高量化模型精度，降低存储量到原始模型的四分之一，降低内存，加速计算（某些模型可能会比float模型慢，因为float的优化方法和int8不同） | LSQ，OAQ，WAQ | | 直接权值量化 | 仅将模型中的权值进行量化，计算时还原为float进行计算，因此仅减少模型存储量，计算速度和float相同，可以在模型转换时一键完成，8bit量化情况下，精度基本不变，模型大小减小到原来的1/4 | 对称量化，非对称量化 | | 训练权值量化 | 特点同直接权值量化，但通过mnncompress压缩算法插件实现，因而可以提供更低比特的权值量化，以减少更多的存储量，并提高权值量化之后模型的精度，例如4bit量化情况下，模型大小减小到原来的1/8 | 对称量化 | -| FP16 | 将FP32计算转换为FP16计算，可在模型转换时一键完成，模型大小减小为原来的1/2，精度基本无损 | - | +| FP16 | 将FP32的权重转换成FP16的类型，可在模型转换时一键完成，模型大小减小为原来的1/2，精度基本无损 | - | ### 怎么用？ 1. 使用模型转换工具中的压缩功能无需额外数据，只要在模型转换时加对应参数即可，开启动态量化功能后也可以对卷积等计算量大的算子实现量化加速。 @@ -64,19 +64,42 @@ MNN模型压缩工具提供了包括低秩分解、剪枝、量化等模型压 --weightQuantBits 8 [--weightQuantAsymmetric](可选) [--weightQuantBlock 128](可选) ``` `--weightQuantAsymmetric` 选项是指使用非对称量化方法，精度要比默认的对称量化精度好一些。 -`--weightQuantBlock 128` 表示以128为单位进行量化，如不设置则以输入通道数为单位进行量化。如果牺牲一些存储大小来提升量化精度，可以增加这个设置，理论上越小精度越高，但建议不要低于32。 +`--weightQuantBlock 128` 表示以128为单位进行量化，如不设置则以输入通道数为单位进行量化。若希望牺牲一些存储空间来提升量化精度，可以增加这个设置。理论上越小精度越高，但不能低于32。 + - 动态量化 可以通过如下方式打开MNN运行时的动态量化支持，使权值量化后的模型中卷积等核心算子使用量化计算，降低内存并提升性能 + 1. 打开 MNN_LOW_MEMORY 编译宏编译 MNN （支持动态量化功能） +``` +cmake .. -DMNN_LOW_MEMORY=ON +``` + 2. 使用 mnn 模型时 memory mode 设成 low +``` +MNN::ScheduleConfig config; +BackendConfig backendConfig; +backendConfig.memory = BackendConfig::Memory_Low; +config.backendConfig = &backendConfig; +``` + ### FP16压缩 -- 将模型中FP32权值转换为FP16存储，并在支持的设备上开启FP16推理，可以获得推理加速，并且速度减少到原来的1/2。可以在模型转换时一键完成，使用方便。 +- 将模型中FP32权值转换为FP16存储，大小减少到原来的1/2。 - 使用`MNNConvert`（c++）或者`mnnconvert`（python包中自带）进行转换，转换命令行中加上下述选项即可： ```bash --fp16 ``` +注意：FP16压缩与FP16加速无关，只要设置 precision = low ，无论 FP32 还是 FP16 的模型，MNN 都会在支持的设备上启用FP16加速功能 + +``` +MNN::ScheduleConfig config; +BackendConfig backendConfig; +backendConfig.precision = BackendConfig::Precision_Low; +config.backendConfig = &backendConfig; +``` + + ## 离线量化工具 ### 离线量化工具安装 - c++工具安装 diff --git a/express/Executor.cpp b/express/Executor.cpp index 6c370d6a4..70800b505 100644 --- a/express/Executor.cpp +++ b/express/Executor.cpp @@ -233,6 +233,13 @@ void Executor::RuntimeManager::setHint(Interpreter::HintMode mode, int value) { void Executor::RuntimeManager::setExternalPath(std::string path, int type) { mInside->modes.setExternalPath(path, type); } +void Executor::RuntimeManager::setHintPtr(Interpreter::HintMode mode, void* value) { + auto current = ExecutorScope::Current(); + auto rt = current->getRuntime(); + for (auto& iter : rt.first) { + iter.second->pMeta = value; + } +} bool Executor::RuntimeManager::getInfo(Interpreter::SessionInfoCode code, void* ptr) { // Only support get memory diff --git a/include/MNN/Interpreter.hpp b/include/MNN/Interpreter.hpp index 19bb95407..bffb2f313 100644 --- a/include/MNN/Interpreter.hpp +++ b/include/MNN/Interpreter.hpp @@ -236,6 +236,12 @@ class MNN_PUBLIC Interpreter { KVCACHE_SIZE_LIMIT = 8, // Op encoder number for commit OP_ENCODER_NUMBER_FOR_COMMIT = 9, + + // KVCache Info + KVCACHE_INFO = 10, + // mmap allocate file size, KB + MMAP_FILE_SIZE = 11, + USE_CACHED_MMAP = 12 }; enum ExternalPathType { diff --git a/include/MNN/MNNDefine.h b/include/MNN/MNNDefine.h index bd0b72a30..91e7877a8 100644 --- a/include/MNN/MNNDefine.h +++ b/include/MNN/MNNDefine.h @@ -75,6 +75,6 @@ MNN_ERROR("Check failed: %s ==> %s\n", #success, #log); \ #define STR(x) STR_IMP(x) #define MNN_VERSION_MAJOR 3 #define MNN_VERSION_MINOR 0 -#define MNN_VERSION_PATCH 2 +#define MNN_VERSION_PATCH 3 #define MNN_VERSION STR(MNN_VERSION_MAJOR) "." STR(MNN_VERSION_MINOR) "." STR(MNN_VERSION_PATCH) #endif /* MNNDefine_h */ diff --git a/include/MNN/expr/Executor.hpp b/include/MNN/expr/Executor.hpp index 3022f7b9d..eab957330 100644 --- a/include/MNN/expr/Executor.hpp +++ b/include/MNN/expr/Executor.hpp @@ -125,6 +125,7 @@ class MNN_PUBLIC Executor { friend class Executor; void setMode(Interpreter::SessionMode mode); void setHint(Interpreter::HintMode mode, int value); + void setHintPtr(Interpreter::HintMode mode, void* value); bool getInfo(Interpreter::SessionInfoCode code, void* ptr); BackendConfig* getBnConfig(); const RuntimeAttr* getInside() const { diff --git a/project/android/build_32.sh b/project/android/build_32.sh index 24f0eb8cc..9f9c8b5a1 100755 --- a/project/android/build_32.sh +++ b/project/android/build_32.sh @@ -9,6 +9,7 @@ cmake ../../../ \ -DMNN_USE_LOGCAT=false \ -DMNN_USE_SSE=OFF \ -DMNN_BUILD_TEST=ON \ +-DMNN_ARM82=OFF \ -DMNN_BUILD_FOR_ANDROID_COMMAND=true \ -DNATIVE_LIBRARY_OUTPUT=. -DNATIVE_INCLUDE_OUTPUT=. $1 $2 $3 $4 $5 $6 $7 diff --git a/pymnn/src/llm.h b/pymnn/src/llm.h index 93329cd60..0b7521918 100644 --- a/pymnn/src/llm.h +++ b/pymnn/src/llm.h @@ -52,6 +52,25 @@ static PyObject* PyMNNLLM_generate(LLM *self, PyObject *args) { return toPyObj(output_ids); } +static PyObject* PyMNNLLM_eraseHistory(LLM *self, PyObject *args) { + if (self->is_embedding) { + Py_RETURN_NONE; + } + size_t history = 0; + size_t end = 0; + if (!PyArg_ParseTuple(args, "LL", &history, &end)) { + Py_RETURN_NONE; + } + self->llm->eraseHistory(history, end); + Py_RETURN_NONE; +} +static PyObject* PyMNNLLM_getCurrentHistory(LLM *self, PyObject *args) { + if (self->is_embedding) { + Py_RETURN_NONE; + } + auto history = self->llm->getCurrentHistory(); + return PyLong_FromLong(history); +} static PyObject* PyMNNLLM_response(LLM *self, PyObject *args) { if (self->is_embedding) { Py_RETURN_NONE; @@ -62,8 +81,8 @@ static PyObject* PyMNNLLM_response(LLM *self, PyObject *args) { Py_RETURN_NONE; } std::ostringstream null_os; - auto res = self->llm->response(query, stream ? &std::cout : &null_os); - return string2Object(res); + self->llm->response(query, stream ? &std::cout : &null_os); + return string2Object(null_os.str()); } static PyObject* PyMNNLLM_tokenizer_encode(LLM *self, PyObject *args) { @@ -109,6 +128,8 @@ static PyMethodDef PyMNNLLM_methods[] = { {"forward", (PyCFunction)PyMNNLLM_forward, METH_VARARGS, "forward `logits` by `input_ids`."}, {"generate", (PyCFunction)PyMNNLLM_generate, METH_VARARGS, "generate `output_ids` by `input_ids`."}, {"response", (PyCFunction)PyMNNLLM_response, METH_VARARGS, "response `query` without hsitory."}, + {"get_current_history", (PyCFunction)PyMNNLLM_getCurrentHistory, METH_VARARGS, "Get Current History."}, + {"erase_history", (PyCFunction)PyMNNLLM_eraseHistory, METH_VARARGS, "Erase History."}, {"tokenizer_encode", (PyCFunction)PyMNNLLM_tokenizer_encode, METH_VARARGS, "tokenizer encode."}, {"tokenizer_decode", (PyCFunction)PyMNNLLM_tokenizer_decode, METH_VARARGS, "tokenizer decode."}, {"txt_embedding", (PyCFunction)PyMNNLLM_txt_embedding, METH_VARARGS, "txt embedding."}, diff --git a/source/backend/cpu/CPUAttention.cpp b/source/backend/cpu/CPUAttention.cpp index 2ebc3d174..c2ab4b008 100644 --- a/source/backend/cpu/CPUAttention.cpp +++ b/source/backend/cpu/CPUAttention.cpp @@ -177,7 +177,7 @@ ErrorCode CPUAttention::onResize(const std::vector& inputs, const std:: backend()->onAcquireBuffer(mPackQ.get(), Backend::DYNAMIC); backend()->onAcquireBuffer(mPackQKV.get(), Backend::DYNAMIC); backend()->onReleaseBuffer(mPackQ.get(), Backend::DYNAMIC); - backend()->onReleaseBuffer(mPackQKV.get(), Backend::DYNAMIC); + backend()->onReleaseBuffer(mPackQKV.get(), Backend::DYNAMIC); } return NO_ERROR; } @@ -193,9 +193,6 @@ ErrorCode CPUAttention::onExecute(const std::vector& inputs, const std: int mask_kvlen = mask->length(3); int seq_len = query->length(1); MNN_ASSERT(seq_len == mask_seqlen); - mIsPrefill = (seq_len > 1); - // isPrefill and mask is Square Matrix, is FirstPrefill - mIsFirstPrefill = mIsPrefill && (mask_kvlen == mask_seqlen); int tileCount = UP_DIV(mNumHead, mThreadNum); int group_size = mNumHead / mKvNumHead; // reduce the value of 'query' to avoid fp16 overflow @@ -215,15 +212,12 @@ ErrorCode CPUAttention::onExecute(const std::vector& inputs, const std: mScale /= q_scale; } - if (mIsPrefill) { - if (mIsFirstPrefill) { - mKVCacheManager->onClear(); - mKVCacheManager->onAlloc(seq_len); - } else { - mKVCacheManager->onRealloc(mKVCacheManager->kvLength() + seq_len); - } - } else { // Decode - mKVCacheManager->onRealloc(mKVCacheManager->kvLength() + 1); + if (mMeta->previous == mMeta->remove) { + mKVCacheManager->onClear(); + mKVCacheManager->onAlloc(mMeta->add); + } else { + MNN_ASSERT(mMeta->previous == mKVCacheManager->kvLength()); + mKVCacheManager->onRealloc(mMeta); } // Add the new kv to the kvcache mKVCacheManager->onPushBack(key, value); @@ -383,6 +377,7 @@ bool CPUAttention::onClone(Backend* bn, const Op* op, Execution** dst) { } CPUAttention::CPUAttention(Backend *backend, bool kv_cache) : Execution(backend), mKVCache(kv_cache) { + mMeta = (KVMeta*)(backend->getRuntime()->pMeta); if (mKVCache) { mPackQ.reset(Tensor::createDevice({1, 1, 1, 1})); mPackQKV.reset(Tensor::createDevice({1, 1, 1, 1})); diff --git a/source/backend/cpu/CPUAttention.hpp b/source/backend/cpu/CPUAttention.hpp index a05b68712..066d925cd 100644 --- a/source/backend/cpu/CPUAttention.hpp +++ b/source/backend/cpu/CPUAttention.hpp @@ -13,6 +13,7 @@ #include #include "core/Execution.hpp" +#include "core/OpCommonUtils.hpp" #include "MNN/ErrorCode.hpp" #include "KVCacheManager.hpp" @@ -26,8 +27,6 @@ class CPUAttention : public Execution { virtual ErrorCode onExecute(const std::vector &inputs, const std::vector &outputs) override; virtual bool onClone(Backend* bn, const Op* op, Execution** dst) override; private: - bool mIsPrefill = true; - bool mIsFirstPrefill = true; bool mKVCache = true; bool mUseGemmInt8 = false; int bytes = 4; @@ -40,6 +39,7 @@ class CPUAttention : public Execution { std::vector mMinQ, mMaxQ, mQueryScale, mQueryZeroPoint; template void pack_query(Tensor* query, char* pack_q, char* sum_q, int seq_len, int h, float q_scale); template void unpack_QK(float * unpack_qk_dst, char * pack_qk_src, int seq_len, int kv_seq_len); + KVMeta* mMeta; }; } // namespace MNN diff --git a/source/backend/cpu/CPUBackend.cpp b/source/backend/cpu/CPUBackend.cpp index 4c4cb7873..9720e132f 100644 --- a/source/backend/cpu/CPUBackend.cpp +++ b/source/backend/cpu/CPUBackend.cpp @@ -19,6 +19,7 @@ #include "CPUCast.hpp" #include "core/OpCommonUtils.hpp" #include "core/WrapExecution.hpp" +#include "core/MNNFileUtils.h" #ifdef _OPENMP #include #endif // _OPENMP @@ -194,6 +195,7 @@ CPURuntime::CPURuntime(const Backend::Info& info) { MNN_PRINT("create CPURuntime:%p\n", this); #endif } + CPURuntime:: ~ CPURuntime() { #ifdef MNN_USE_THREAD_POOL ThreadPool::releaseWorkIndex(mTaskIndex); @@ -223,18 +225,31 @@ Backend* CPURuntime::onCreate(const BackendConfig* config, Backend* origin) cons if (mDynamicMmap.empty()) { // Only support set featuremap dir once mDynamicMmap.resize(2); - auto mmapMem = BufferAllocator::Allocator::createMmap(hint().midMemoryPath.c_str(), "dynamic"); + auto mmapMem = BufferAllocator::Allocator::createMmap(hint().midMemoryPath.c_str(), "", "dynamic"); for (auto& buf : mDynamicMmap) { buf.root = mmapMem; } } } if (hint().weightMemoryPath.size() > 0) { + // forward_type, precision_type, memory_type, power_type + std::string prefix = "0_0_0_0_"; + prefix[2] += mPrecision; + prefix[4] += mMemory; + prefix[6] += mPower; + // prefix += hint().modelUUID + "_"; + bool autoRemove = true; + if (hint().useCachedMmap) { + autoRemove = false; + std::string fileName = MNNFilePathConcat(hint().weightMemoryPath, prefix + "0.static"); + const_cast(hint()).useCachedMmap += MNNFileExist(fileName.c_str()); + } if (nullptr == mStaticAllocatorCache.get()) { // Only support set weightmap dir once mStaticAllocatorCache = mStaticAllocator; - auto mmapMem = BufferAllocator::Allocator::createMmap(hint().weightMemoryPath.c_str(), "static"); - mStaticAllocator.reset(new EagerBufferAllocator(mmapMem, 32, 1024 * 1024 * 1024)); + auto mmapMem = BufferAllocator::Allocator::createMmap(hint().weightMemoryPath.c_str(), prefix.c_str(), "static", autoRemove); + int mmapSize = hint().mmapFileSize * 1024 * 1024; + mStaticAllocator.reset(new EagerBufferAllocator(mmapMem, 32, mmapSize)); } } auto precision = mPrecision; @@ -551,7 +566,7 @@ static OpType _getRealOpType(OpType opType) { return OpType_DepthwiseConvInt8; case OpType_Pooling: return OpType_PoolInt8; - + // case OpType_Eltwise: // // TODO: just support EltwiseAdd // return OpType_EltwiseInt8; diff --git a/source/backend/cpu/CPUStft.cpp b/source/backend/cpu/CPUStft.cpp index 5e6d40b54..41b42a28d 100644 --- a/source/backend/cpu/CPUStft.cpp +++ b/source/backend/cpu/CPUStft.cpp @@ -7,7 +7,10 @@ // #ifdef MNN_BUILD_AUDIO - +#ifndef M_PI +#define M_PI 3.141592654 +#endif +#include #include "backend/cpu/CPUStft.hpp" #include "backend/cpu/CPUBackend.hpp" #include "core/Concurrency.h" @@ -16,6 +19,21 @@ #include "compute/CommonOptFunction.h" namespace MNN { +static void MNNDftAbs(const float* input, const float* window, float* output, float* buffer, int nfft) { + for (int i = 0; i < nfft; ++i) { + buffer[i] = input[i] * window[i]; + } + for (int k = 0; k < nfft / 2 + 1; ++k) { + float real_sum = 0.f, imag_sum = 0.f; + for (int n = 0; n < nfft; ++n) { + float angle = 2 * M_PI * k * n / nfft; + real_sum += buffer[n] * std::cos(angle); + imag_sum -= buffer[n] * std::sin(angle); + } + output[k] = std::sqrt(real_sum * real_sum + imag_sum * imag_sum); + } +} + CPUStft::CPUStft(Backend* backend, int nfft, int hop_length, bool abs) : Execution(backend), mNfft(nfft), mHopLength(hop_length), mAbs(abs) { @@ -72,4 +90,4 @@ class CPUStftCreator : public CPUBackend::Creator { REGISTER_CPU_OP_CREATOR_AUDIO(CPUStftCreator, OpType_Stft); } // namespace MNN -#endif // MNN_BUILD_AUDIO \ No newline at end of file +#endif // MNN_BUILD_AUDIO diff --git a/source/backend/cpu/KVCacheManager.cpp b/source/backend/cpu/KVCacheManager.cpp index a38a2137d..a282b27fa 100644 --- a/source/backend/cpu/KVCacheManager.cpp +++ b/source/backend/cpu/KVCacheManager.cpp @@ -386,73 +386,133 @@ void KVCacheManager::onAlloc(int kv_seq_len) { } } -void KVCacheManager::onRealloc(int kv_seq_len) { - if (kv_seq_len <= mMaxLength) { - return; - } - int oldMaxLength = mMaxLength; - mMaxLength = kv_seq_len + mConfig.mExpandChunk; - size_t oldKeySize, oldValueSize, keySize, valueSize; - if (mConfig.mUseInt8Kernel) { - oldKeySize = (size_t)mKvNumHead * UP_DIV(oldMaxLength, hP8) * UP_DIV(mHeadDim, lP8) * hP8 * lP8; - keySize = (size_t)mKvNumHead * UP_DIV(mMaxLength, hP8) * UP_DIV(mHeadDim, lP8) * hP8 * lP8; - } else if (mConfig.mQuantKey) { - oldKeySize = (size_t)mKvNumHead * UP_DIV(oldMaxLength, hP) * mHeadDim * hP; - keySize = (size_t)mKvNumHead * UP_DIV(mMaxLength, hP) * mHeadDim * hP; - } else { - oldKeySize = (size_t)mKvNumHead * UP_DIV(oldMaxLength, hP) * mHeadDim * hP * mBytes; - keySize = (size_t)mKvNumHead * UP_DIV(mMaxLength, hP) * mHeadDim * hP * mBytes; - } - oldValueSize = (size_t)mKvNumHead * UP_DIV(mHeadDim, hP) * oldMaxLength * hP * (mConfig.mQuantValue ? 1 : mBytes); - valueSize = (size_t)mKvNumHead * UP_DIV(mHeadDim, hP) * mMaxLength * hP * (mConfig.mQuantValue ? 1 : mBytes); - /*==== No limit for kvcache ====*/ - if (mConfig.mKVCacheSizeLimit == -1) { - expandKVCacheInMem(oldMaxLength); - } - /*==== Last time the kvcache is memory, now it should be in memory too ====*/ - else if (keySize + valueSize <= mConfig.mKVCacheSizeLimit) { - expandKVCacheInMem(oldMaxLength); - } - /*==== Last time the kvcache is in memory, but now it should be moved to disk ====*/ - else if (oldKeySize + oldValueSize <= mConfig.mKVCacheSizeLimit) { - createKVCacheFile(); - resetKVCacheFileSize(keySize, valueSize); - mmapKVCache(keySize, valueSize); - moveKVCacheFromMemToDisk(oldMaxLength); - mKVCacheInDisk = true; +void KVCacheManager::onRealloc(const KVMeta* meta) { + auto kv_seq_len = meta->previous + meta->add - meta->remove + meta->computeReverseSize(); + if (kv_seq_len > mMaxLength) { + // Realloc + int oldMaxLength = mMaxLength; + mMaxLength = kv_seq_len + mConfig.mExpandChunk; + size_t oldKeySize, oldValueSize, keySize, valueSize; + if (mConfig.mUseInt8Kernel) { + oldKeySize = (size_t)mKvNumHead * UP_DIV(oldMaxLength, hP8) * UP_DIV(mHeadDim, lP8) * hP8 * lP8; + keySize = (size_t)mKvNumHead * UP_DIV(mMaxLength, hP8) * UP_DIV(mHeadDim, lP8) * hP8 * lP8; + } else if (mConfig.mQuantKey) { + oldKeySize = (size_t)mKvNumHead * UP_DIV(oldMaxLength, hP) * mHeadDim * hP; + keySize = (size_t)mKvNumHead * UP_DIV(mMaxLength, hP) * mHeadDim * hP; + } else { + oldKeySize = (size_t)mKvNumHead * UP_DIV(oldMaxLength, hP) * mHeadDim * hP * mBytes; + keySize = (size_t)mKvNumHead * UP_DIV(mMaxLength, hP) * mHeadDim * hP * mBytes; + } + oldValueSize = (size_t)mKvNumHead * UP_DIV(mHeadDim, hP) * oldMaxLength * hP * (mConfig.mQuantValue ? 1 : mBytes); + valueSize = (size_t)mKvNumHead * UP_DIV(mHeadDim, hP) * mMaxLength * hP * (mConfig.mQuantValue ? 1 : mBytes); + /*==== No limit for kvcache ====*/ + if (mConfig.mKVCacheSizeLimit == -1) { + expandKVCacheInMem(oldMaxLength); + } + /*==== Last time the kvcache is memory, now it should be in memory too ====*/ + else if (keySize + valueSize <= mConfig.mKVCacheSizeLimit) { + expandKVCacheInMem(oldMaxLength); + } + /*==== Last time the kvcache is in memory, but now it should be moved to disk ====*/ + else if (oldKeySize + oldValueSize <= mConfig.mKVCacheSizeLimit) { + createKVCacheFile(); + resetKVCacheFileSize(keySize, valueSize); + mmapKVCache(keySize, valueSize); + moveKVCacheFromMemToDisk(oldMaxLength); + mKVCacheInDisk = true; + } + /*==== Last time the kvcache is disk, now it should be in disk too ====*/ + else { + expandKVCacheInDisk(oldMaxLength, oldKeySize, oldValueSize, keySize, valueSize); + } + /* No matter where is the kvcache, the scales and zero points are always in memory, since their size is very small */ + if (mConfig.mUseInt8Kernel) { + auto new_scale = Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP8), hP8}); + auto new_zeroPoint = Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP8), hP8}); + auto new_sum = Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP8), hP8}); + mBackend->onAcquireBuffer(new_scale, Backend::STATIC); + mBackend->onAcquireBuffer(new_zeroPoint, Backend::STATIC); + mBackend->onAcquireBuffer(new_sum, Backend::STATIC); + for (int h = 0; h < mKvNumHead; h++) { + memcpy(new_scale->host() + h * UP_DIV(mMaxLength, hP8) * hP8 * 4, mKeyScale->host() + h * UP_DIV(oldMaxLength, hP8) * hP8 * 4, UP_DIV(oldMaxLength, hP8) * hP8 * 4); + memcpy(new_zeroPoint->host() + h * UP_DIV(mMaxLength, hP8) * hP8 * 4, mKeyZeroPoint->host() + h * UP_DIV(oldMaxLength, hP8) * hP8 * 4, UP_DIV(oldMaxLength, hP8) * hP8 * 4); + memcpy(new_sum->host() + h * UP_DIV(mMaxLength, hP8) * hP8 * 4, mKeySum->host() + h * UP_DIV(oldMaxLength, hP8) * hP8 * 4, UP_DIV(oldMaxLength, hP8) * hP8 * 4); + } + mKeyScale.reset(new_scale); + mKeyZeroPoint.reset(new_zeroPoint); + mKeySum.reset(new_sum); + } else if (mConfig.mQuantKey) { + auto new_scale = Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP), 1, hP}); + auto new_zeroPoint = Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP), 1, hP}); + mBackend->onAcquireBuffer(new_scale, Backend::STATIC); + mBackend->onAcquireBuffer(new_zeroPoint, Backend::STATIC); + for (int h = 0; h < mKvNumHead; h++) { + memcpy(new_scale->host() + h * UP_DIV(mMaxLength, hP) * hP * mBytes, mKeyScale->host() + h * UP_DIV(oldMaxLength, hP) * hP * mBytes, UP_DIV(oldMaxLength, hP) * hP * mBytes); + memcpy(new_zeroPoint->host() + h * UP_DIV(mMaxLength, hP) * hP * mBytes, mKeyZeroPoint->host() + h * UP_DIV(oldMaxLength, hP) * hP * mBytes, UP_DIV(oldMaxLength, hP) * hP * mBytes); + } + mKeyScale.reset(new_scale); + mKeyZeroPoint.reset(new_zeroPoint); + } } - /*==== Last time the kvcache is disk, now it should be in disk too ====*/ - else { - expandKVCacheInDisk(oldMaxLength, oldKeySize, oldValueSize, keySize, valueSize); + // Remove + auto start = mPastLength - meta->remove; + if (0 == meta->n_reserve) { + mPastLength = start; + return; } - /* No matter where is the kvcache, the scales and zero points are always in memory, since their size is very small */ - if (mConfig.mUseInt8Kernel) { - auto new_scale = Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP8), hP8}); - auto new_zeroPoint = Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP8), hP8}); - auto new_sum = Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP8), hP8}); - mBackend->onAcquireBuffer(new_scale, Backend::STATIC); - mBackend->onAcquireBuffer(new_zeroPoint, Backend::STATIC); - mBackend->onAcquireBuffer(new_sum, Backend::STATIC); - for (int h = 0; h < mKvNumHead; h++) { - memcpy(new_scale->host() + h * UP_DIV(mMaxLength, hP8) * hP8 * 4, mKeyScale->host() + h * UP_DIV(oldMaxLength, hP8) * hP8 * 4, UP_DIV(oldMaxLength, hP8) * hP8 * 4); - memcpy(new_zeroPoint->host() + h * UP_DIV(mMaxLength, hP8) * hP8 * 4, mKeyZeroPoint->host() + h * UP_DIV(oldMaxLength, hP8) * hP8 * 4, UP_DIV(oldMaxLength, hP8) * hP8 * 4); - memcpy(new_sum->host() + h * UP_DIV(mMaxLength, hP8) * hP8 * 4, mKeySum->host() + h * UP_DIV(oldMaxLength, hP8) * hP8 * 4, UP_DIV(oldMaxLength, hP8) * hP8 * 4); + // Don't support not align reserve + auto align = hP; + auto dstStart = start; + auto lastValidSrcEnd = start; + for (int n=0; nn_reserve; ++n) { + auto lastEndAlign = UP_DIV(lastValidSrcEnd, align) * align; + auto begin = meta->reserve[2 * n]; + auto size = meta->reserve[2 * n + 1]; + auto startAlign = ((begin + start) / align) * align; + if (startAlign <= lastEndAlign) { + // Fullly reserve + dstStart = dstStart + size; + lastValidSrcEnd = begin + start + size; + continue; } - mKeyScale.reset(new_scale); - mKeyZeroPoint.reset(new_zeroPoint); - mKeySum.reset(new_sum); - } else if (mConfig.mQuantKey) { - auto new_scale = Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP), 1, hP}); - auto new_zeroPoint = Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP), 1, hP}); - mBackend->onAcquireBuffer(new_scale, Backend::STATIC); - mBackend->onAcquireBuffer(new_zeroPoint, Backend::STATIC); - for (int h = 0; h < mKvNumHead; h++) { - memcpy(new_scale->host() + h * UP_DIV(mMaxLength, hP) * hP * mBytes, mKeyScale->host() + h * UP_DIV(oldMaxLength, hP) * hP * mBytes, UP_DIV(oldMaxLength, hP) * hP * mBytes); - memcpy(new_zeroPoint->host() + h * UP_DIV(mMaxLength, hP) * hP * mBytes, mKeyZeroPoint->host() + h * UP_DIV(oldMaxLength, hP) * hP * mBytes, UP_DIV(oldMaxLength, hP) * hP * mBytes); + auto end = begin + start + size; + auto endAlign = UP_DIV(end, align) * align; + + auto sizeUnit = (endAlign - startAlign) / align; + auto dstStartAlign = UP_DIV(dstStart, align) * align; + + //TODO: Support Quant +// mPastKey.reset(Tensor::createDevice({mKvNumHead, UP_DIV(mMaxLength, hP), mHeadDim, hP})); + + // Move K + auto keyStride = UP_DIV(mMaxLength, align) * align * mHeadDim; + auto dstKAddr = keyAddr() + dstStartAlign * mHeadDim * mBytes; + auto srcKAddr = keyAddr() + startAlign * mHeadDim * mBytes; + for (int i=0; i({mKvNumHead, UP_DIV(mHeadDim, hP), mMaxLength, hP})); + + // Move V + auto dstVAddr = valudAddr() + dstStartAlign * align * mBytes; + auto srcVAddr = valudAddr() + startAlign * align * mBytes; + auto number = mKvNumHead * UP_DIV(mHeadDim, align); + for (int i=0; ihost(); + return (uint8_t*)baseAddr; + } + uint8_t* valudAddr() { + char * baseAddr = mKVCacheInDisk ? mMapValueAddr : mPastValue->host(); + return (uint8_t*)baseAddr; + } char * addrOfKey(int kv_h) { char * baseAddr = mKVCacheInDisk ? mMapKeyAddr : mPastKey->host(); if (mConfig.mUseInt8Kernel) { @@ -148,7 +156,7 @@ class KVCacheManager : public NonCopyable{ } void onResize(int kv_num_head, int head_dim); void onAlloc(int kv_seq_len); - void onRealloc(int kv_seq_len); + void onRealloc(const KVMeta* meta); void onClear(); void onPushBack(const Tensor * key, const Tensor * value); void onDequantValue(Tensor * dequantedValues); @@ -158,4 +166,4 @@ class KVCacheManager : public NonCopyable{ #endif // KVCACHE_MANAGER_HPP -#endif // MNN_SUPPORT_TRANSFORMER_FUSE \ No newline at end of file +#endif // MNN_SUPPORT_TRANSFORMER_FUSE diff --git a/source/backend/cpu/compute/CommonOptFunction.cpp b/source/backend/cpu/compute/CommonOptFunction.cpp index 734851753..cbe42ebee 100644 --- a/source/backend/cpu/compute/CommonOptFunction.cpp +++ b/source/backend/cpu/compute/CommonOptFunction.cpp @@ -23,9 +23,6 @@ #include "../CPUBinary.hpp" #include "../CPUUnary.hpp" #include "../CPUPool.hpp" -#ifndef M_PI -#define M_PI 3.141592654 -#endif #define PACK 4 #define FLOAT float using Vec = MNN::Math::Vec; @@ -693,9 +690,7 @@ void MNNAccumulateSequenceNumber (float* dst, const float* src, int size) { src += 8; } sum4_1 = vaddq_f32(sum4_1, sum4_2); - for (int j = 0;j < 4; ++j) { - sum += sum4_1[j]; - } + sum = (sum4_1[0] + sum4_1[1]) + (sum4_1[2] + sum4_1[3]); } #elif defined(MNN_USE_SSE) if (size >= 8) { @@ -3102,21 +3097,6 @@ void MNNSiLuLowp(float* dst, const float* src, size_t dataSize) { #endif } -void MNNDftAbs(const float* input, const float* window, float* output, float* buffer, int nfft) { - for (int i = 0; i < nfft; ++i) { - buffer[i] = input[i] * window[i]; - } - for (int k = 0; k < nfft / 2 + 1; ++k) { - float real_sum = 0.f, imag_sum = 0.f; - for (int n = 0; n < nfft; ++n) { - float angle = 2 * M_PI * k * n / nfft; - real_sum += buffer[n] * std::cos(angle); - imag_sum -= buffer[n] * std::sin(angle); - } - output[k] = std::sqrt(real_sum * real_sum + imag_sum * imag_sum); - } -} - static void _MNNAdjustOptimalSparseKernel(int& sparseBlockOC, MNN::CoreFunctions::MNNPackedSparseMatMul& packedSparseMatMul) { if(sparseBlockOC == 4) { packedSparseMatMul = MNNPackedSparseMatMulEpx4; diff --git a/source/backend/cpu/compute/CommonOptFunction.h b/source/backend/cpu/compute/CommonOptFunction.h index 0159aa286..8065fcfba 100644 --- a/source/backend/cpu/compute/CommonOptFunction.h +++ b/source/backend/cpu/compute/CommonOptFunction.h @@ -101,7 +101,6 @@ void MNNGeluCommon(float* dst, const float* src, size_t size); void MNNGeluStandardCommon(float* dst, const float* src, size_t size); void MNNSoftmax(float* dest, const float* source, size_t size); void MNNNorm(float* dest, const float* source, const float *gamma, const float *beta, float epsilon, size_t size, bool RMSNorm = false); -void MNNDftAbs(const float* input, const float* window, float* output, float* buffer, int nfft); // Get Pack for MatMul's e , l , h , the pack number must be 1 or 4 * n void MNNGetMatMulPackMode(int* eP, int *lP, int* hP); diff --git a/source/backend/cpu/compute/ConvInt8TiledExecutor.cpp b/source/backend/cpu/compute/ConvInt8TiledExecutor.cpp index feb0fd345..1867fa3fd 100644 --- a/source/backend/cpu/compute/ConvInt8TiledExecutor.cpp +++ b/source/backend/cpu/compute/ConvInt8TiledExecutor.cpp @@ -102,7 +102,7 @@ void ConvInt8TiledExecutor::reorderWeight(Tensor* weight, const uint8_t* weightS static bool _reorderWeightInside(Backend* bn, const Convolution2DCommon* common, const std::shared_ptr& weightOrigin, - std::shared_ptr& weight, int blockNum) { + std::shared_ptr& weight, int blockNum, bool alloc) { MNN_ASSERT(blockNum > 0); auto core = static_cast(bn)->int8Functions(); auto gcore = static_cast(bn)->functions(); @@ -118,13 +118,20 @@ static bool _reorderWeightInside(Backend* bn, const Convolution2DCommon* common, } else { shape = {UP_DIV(oc, UNIT), UP_DIV(ic, SRC_UNIT) * kernelCount, UNIT, SRC_UNIT}; } - - weight.reset(Tensor::createDevice(shape)); - - bool succ = bn->onAcquireBuffer(weight.get(), Backend::STATIC); - if (!succ) { - MNN_ERROR("Memory not enough"); - return false; + bool useCachedMmap = bn->getRuntime()->hint().useCachedMmap > 1; + if (alloc) { + weight.reset(Tensor::createDevice(shape)); + bool succ = bn->onAcquireBuffer(weight.get(), Backend::STATIC); + if (!succ) { + MNN_ERROR("Memory not enough"); + return false; + } + } else { + // useCachedMmap don't need alloc memory + weight.reset(useCachedMmap ? Tensor::createDevice(shape) : Tensor::create(shape)); + } + if (useCachedMmap) { + return true; } ConvInt8TiledExecutor::reorderWeight(weight.get(), weightOrigin->host(), SRC_UNIT, UNIT, ic, oc, kernelCount, pack, blockNum); return true; @@ -136,6 +143,7 @@ static void GetResourceInt8(std::shared_ptr resour auto core = static_cast(backend)->functions(); int LSize = conv2d->common()->inputCount() * conv2d->common()->kernelX() * conv2d->common()->kernelY(); int ocUp4 = ROUND_UP(outputCount, core->pack); + bool useCachedMmap = backend->getRuntime()->hint().useCachedMmap > 1; int dequantCnt = quantCommon->alpha.size(); if (quantCommon->asymmetric) { @@ -151,20 +159,13 @@ static void GetResourceInt8(std::shared_ptr resour originOffset = -8; resource->mActBits = 4; } - // Save bias + // alloc memory resource->mOriginBias.reset(Tensor::createDevice({ocUp4})); // float auto success = backend->onAcquireBuffer(resource->mOriginBias.get(), Backend::STATIC); if (!success) { MNN_ERROR("Alloc bias memory error\n"); return; } - ::memset(resource->mOriginBias->host(), 0, ocUp4 * sizeof(float)); - if (conv2d->bias()) { - ::memcpy(resource->mOriginBias->host(), conv2d->bias()->data(), outputCount * sizeof(float)); - } else { - ::memset(resource->mOriginBias->host(), 0, ocUp4 * sizeof(float)); - } - // Save weight quant alpha and zero: wf=alpha*wi+zero int bytes = 4; resource->mOriginScale.reset(Tensor::createDevice({2 * scaleSize * bytes})); success = backend->onAcquireBuffer(resource->mOriginScale.get(), Backend::STATIC); @@ -172,6 +173,23 @@ static void GetResourceInt8(std::shared_ptr resour MNN_ERROR("Alloc denquant alpha, zero memory error\n"); return; } + resource->mWeightKernelSum.reset(Tensor::createDevice({bytes * ocUp4})); + success = backend->onAcquireBuffer(resource->mWeightKernelSum.get(), Backend::STATIC); + if (!success) { + MNN_ERROR("Alloc denquant weight kernel sum memory error\n"); + return; + } + if (useCachedMmap) { + return; + } + // Save bias + ::memset(resource->mOriginBias->host(), 0, ocUp4 * sizeof(float)); + if (conv2d->bias()) { + ::memcpy(resource->mOriginBias->host(), conv2d->bias()->data(), outputCount * sizeof(float)); + } else { + ::memset(resource->mOriginBias->host(), 0, ocUp4 * sizeof(float)); + } + // Save weight quant alpha and zero: wf=alpha*wi+zero auto alphaPtr = resource->mOriginScale->host(); auto biasPtr = reinterpret_cast(reinterpret_cast(alphaPtr) + scaleSize * bytes); if (outputCount % core->pack != 0) { @@ -202,12 +220,6 @@ static void GetResourceInt8(std::shared_ptr resour } } // Save float weight kernel sum - resource->mWeightKernelSum.reset(Tensor::createDevice({bytes * ocUp4})); - success = backend->onAcquireBuffer(resource->mWeightKernelSum.get(), Backend::STATIC); - if (!success) { - MNN_ERROR("Alloc denquant weight kernel sum memory error\n"); - return; - } auto weightKernelSum = resource->mWeightKernelSum->host(); auto realWeightData = quantCommon->weight.get(); ::memset(weightKernelSum, 0, resource->mWeightKernelSum->size()); @@ -266,7 +278,7 @@ DenseConvInt8TiledExecutor::DenseConvInt8TiledExecutor(Backend* backend, const O int oc = convOp->common()->outputCount(); int ic = convOp->common()->inputCount(); bool directReadInt4weight = (kernelCount == 1 && ROUND_UP(oc, UNIT) == oc && ROUND_UP(ic, SRC_UNIT) == ic); - + bool useCachedMmap = backend->getRuntime()->hint().useCachedMmap > 1; #ifdef MNN_KLEIDIAI_ENABLED bool half_act = gcore->bytes == 2; int biasSize = mResourceInt8->mOriginBias->size(); @@ -323,44 +335,42 @@ DenseConvInt8TiledExecutor::DenseConvInt8TiledExecutor(Backend* backend, const O MNN_ERROR("int4 weight acquire buffer error\n"); return ; } - auto srcPtr = (uint8_t*)quanCommon->weight.get(); - auto dstPtr = mResourceInt8->mWeightInt8->host(); - ::memset(dstPtr, 0, mResourceInt8->mWeightInt8->size()); - - // Pack two int4-weight to one int8-weight. - int cnt = lP * hP / 4; - int L = lU * lP; - int blockL = lU / blockNum; - int stride0 = (lP * hP) * hU * blockL; - int stride1 = (lP * hP) * blockL; - for (int i = 0; i < hU; ++i) { - for (int j = 0; j < lU; ++j) { - int blockId = j / blockL; - int blockkInsideId = j % blockL; - for (int k = 0; k < cnt; ++k) { - int dstIndx0 = (blockId * stride0 + i * stride1 + blockkInsideId * lP * hP) / 2 + (2 * k); - - int hpId0 = (2 * k + 1) / lP; - int lpId0 = (2 * k) % lP; - int hpId1 = (2 * (k + cnt) + 1) / lP; - int lpId1 = (2 * (k + cnt)) % lP; - int srcIndx0 = ((i * hP + hpId0) * L + (j * lP + lpId0)) / 2; - int srcIndx1 = ((i * hP + hpId1) * L + (j * lP + lpId1)) / 2; - int s0 = (srcPtr[srcIndx0] >> 4); - int s1 = (srcPtr[srcIndx0] & 15); - int s2 = (srcPtr[srcIndx1] >> 4); - int s3 = (srcPtr[srcIndx1] & 15); - int d0 = s0 * 16 + s2; - int d1 = s1 * 16 + s3; - - dstPtr[dstIndx0] = d0; - dstPtr[dstIndx0 + 1] = d1; + if (!useCachedMmap) { + auto srcPtr = (uint8_t*)quanCommon->weight.get(); + auto dstPtr = mResourceInt8->mWeightInt8->host(); + ::memset(dstPtr, 0, mResourceInt8->mWeightInt8->size()); + // Pack two int4-weight to one int8-weight. + int cnt = lP * hP / 4; + int L = lU * lP; + int blockL = lU / blockNum; + int stride0 = (lP * hP) * hU * blockL; + int stride1 = (lP * hP) * blockL; + for (int i = 0; i < hU; ++i) { + for (int j = 0; j < lU; ++j) { + int blockId = j / blockL; + int blockkInsideId = j % blockL; + for (int k = 0; k < cnt; ++k) { + int dstIndx0 = (blockId * stride0 + i * stride1 + blockkInsideId * lP * hP) / 2 + (2 * k); + int hpId0 = (2 * k + 1) / lP; + int lpId0 = (2 * k) % lP; + int hpId1 = (2 * (k + cnt) + 1) / lP; + int lpId1 = (2 * (k + cnt)) % lP; + int srcIndx0 = ((i * hP + hpId0) * L + (j * lP + lpId0)) / 2; + int srcIndx1 = ((i * hP + hpId1) * L + (j * lP + lpId1)) / 2; + int s0 = (srcPtr[srcIndx0] >> 4); + int s1 = (srcPtr[srcIndx0] & 15); + int s2 = (srcPtr[srcIndx1] >> 4); + int s3 = (srcPtr[srcIndx1] & 15); + int d0 = s0 * 16 + s2; + int d1 = s1 * 16 + s3; + dstPtr[dstIndx0] = d0; + dstPtr[dstIndx0 + 1] = d1; + } } } } } else { // std::shared_ptr srcWeight; - if (quanCommon->canUseInt4) { mResourceInt8->mWeightAsymmetricQuant = true; auto srcPtr = reinterpret_cast(quanCommon->weight.get()); @@ -372,34 +382,39 @@ DenseConvInt8TiledExecutor::DenseConvInt8TiledExecutor(Backend* backend, const O tmpWeight[2 * i + 1] = s1; } std::shared_ptr srcWeight(Tensor::create({weightLength * 2}, (void*)tmpWeight.data())); - mValid = _reorderWeightInside(backend, convOp->common(), srcWeight, mResourceInt8->mWeightInt8, blockNum); + std::shared_ptr tmpWeightInt8; + mValid = _reorderWeightInside(backend, convOp->common(), srcWeight, tmpWeightInt8, blockNum, false); if(!mValid) { return; } - MNN_ASSERT(mResourceInt8->mWeightInt8->size() % 2 == 0); - int leng = mResourceInt8->mWeightInt8->size(); + MNN_ASSERT(tmpWeightInt8->size() % 2 == 0); + int leng = tmpWeightInt8->size(); int halflen = leng / 2; - std::shared_ptr weightLow(Tensor::create({halflen})); - auto dstint4Ptr = weightLow->host(); - auto srcint4Ptr = mResourceInt8->mWeightInt8->host(); - int permuteUnit = UNIT * SRC_UNIT; - int halfPermuteStride = static_cast(permuteUnit / 2); - for (int i = 0; i < leng / permuteUnit; ++i) { - auto src0 = srcint4Ptr + i * permuteUnit; - auto dst0 = dstint4Ptr + i * halfPermuteStride; - for (int j = 0; j < halfPermuteStride; ++j) { - int s0 = src0[j]; - int s1 = src0[j + halfPermuteStride]; - int d = (s0 + 8) * 16 + (s1 + 8); - dst0[j] = d; + mResourceInt8->mWeightInt8.reset(Tensor::createDevice({halflen})); + bool succ = backend->onAcquireBuffer(mResourceInt8->mWeightInt8.get(), Backend::STATIC); + if (!succ) { + MNN_ERROR("Memory not enough"); + return; + } + if (!useCachedMmap) { + auto srcint4Ptr = tmpWeightInt8->host(); + auto dstint4Ptr = mResourceInt8->mWeightInt8->host(); + int permuteUnit = UNIT * SRC_UNIT; + int halfPermuteStride = static_cast(permuteUnit / 2); + for (int i = 0; i < leng / permuteUnit; ++i) { + auto src0 = srcint4Ptr + i * permuteUnit; + auto dst0 = dstint4Ptr + i * halfPermuteStride; + for (int j = 0; j < halfPermuteStride; ++j) { + int s0 = src0[j]; + int s1 = src0[j + halfPermuteStride]; + int d = (s0 + 8) * 16 + (s1 + 8); + dst0[j] = d; + } } } - - // Update int4 weight to mWeightInt8. - mResourceInt8->mWeightInt8 = weightLow; } else { std::shared_ptr srcWeight(Tensor::create({weightLength}, (void*)quanCommon->weight.get())); - mValid = _reorderWeightInside(backend, convOp->common(), srcWeight, mResourceInt8->mWeightInt8, blockNum); + mValid = _reorderWeightInside(backend, convOp->common(), srcWeight, mResourceInt8->mWeightInt8, blockNum, true); if(!mValid) { return; } @@ -471,7 +486,7 @@ static void _computeAlphaScale(Backend* backend, const Convolution2D* conv2d, st DenseConvInt8TiledExecutor::DenseConvInt8TiledExecutor(Backend* backend, const Op* op, std::shared_ptr res) : ConvInt8TiledExecutor(backend, op, res) { std::shared_ptr weightOrigin = mResourceInt8->mWeightInt8; auto convOp = op->main_as_Convolution2D(); - mValid = _reorderWeightInside(backend, convOp->common(), weightOrigin, mResourceInt8->mWeightInt8, mBlockNum); + mValid = _reorderWeightInside(backend, convOp->common(), weightOrigin, mResourceInt8->mWeightInt8, mBlockNum, true); if(!mValid) { return; } @@ -1255,4 +1270,4 @@ ErrorCode DenseConvInt8TiledExecutor::onExecute(const std::vector& inpu -} // namespace MNN \ No newline at end of file +} // namespace MNN diff --git a/source/backend/cpu/compute/Convolution1x1Strassen.cpp b/source/backend/cpu/compute/Convolution1x1Strassen.cpp index 455e9cb6c..f149532fe 100644 --- a/source/backend/cpu/compute/Convolution1x1Strassen.cpp +++ b/source/backend/cpu/compute/Convolution1x1Strassen.cpp @@ -59,6 +59,9 @@ Convolution1x1Strassen::Convolution1x1Strassen(const Convolution2DCommon *common MNN_ERROR("Not Enough Memory\n"); return; } + if (b->getRuntime()->hint().useCachedMmap > 1) { + return; + } if (core->bytes < 4) { AutoRelease tempTensor(Tensor::createDevice({outputCount * mSrcCount})); mValid = b->onAcquireBuffer(tempTensor.get(), Backend::STATIC); diff --git a/source/backend/metal/AllShader.cpp b/source/backend/metal/AllShader.cpp index afb0c6fda..ba24d1472 100644 --- a/source/backend/metal/AllShader.cpp +++ b/source/backend/metal/AllShader.cpp @@ -1704,6 +1704,35 @@ const char* shader_MetalConvolution1x1_metal = " if (computeSize>2) {xy_out[2]=activate(M4(result2),cst.activation); }\n" " if (computeSize>3) {xy_out[3]=activate(M4(result3),cst.activation); }\n" "}\n" +"kernel void conv1x1_z4_sg(const device M4 *in [[buffer(0)]],\n" +" device M4 *out [[buffer(1)]],\n" +" constant conv1x1_constants& cst [[buffer(2)]],\n" +" const device M4x4 *wt [[buffer(3)]],\n" +" const device M4 *biasTerms [[buffer(4)]],\n" +" uint3 gid[[threadgroup_position_in_grid]],\n" +" uint tiisg[[thread_index_in_simdgroup]],\n" +" uint sgitg[[simdgroup_index_in_threadgroup]]) {\n" +" if ((int)gid.x >= cst.output_size || (int)gid.y >= cst.output_slice || (int)gid.z >= cst.batch) return;\n" +" \n" +" int rx=gid.x;\n" +" int uz=gid.y;\n" +" auto xy_wt=wt+uz*cst.input_slice;\n" +" auto xy_in0=in+(int)gid.z*cst.input_size+rx+0;\n" +" auto xy_out=out+(int)gid.z*cst.output_size+uz*cst.output_size*cst.batch+rx;\n" +" auto biasValue=FLOAT4(biasTerms[uz]);\n" +" FLOAT4 result0=0;\n" +" int computeSize=min(cst.output_size-rx,CONV_UNROLL);\n" +" for (auto z=tiisg; z3) {xy_out[3]=activate(M4(result3),cst.activation); }\n" "}\n" -"kernel void conv1x1_gemm_16x16_w4(const device M4 *in [[buffer(0)]],\n" +"kernel void conv1x1_gemm_16x16_w4_sg(const device M4 *in [[buffer(0)]],\n" " device M4 *out [[buffer(1)]],\n" " constant conv1x1_constants& cst [[buffer(2)]],\n" " const device uchar2 *wt [[buffer(3)]],\n" @@ -1842,7 +1871,7 @@ const char* shader_MetalConvolution1x1_metal = " }\n" " }\n" "}\n" -"kernel void conv1x1_gemm_32x16_w4(const device M4 *in [[buffer(0)]],\n" +"kernel void conv1x1_gemm_32x16_w4_sg(const device M4 *in [[buffer(0)]],\n" " device M4 *out [[buffer(1)]],\n" " constant conv1x1_constants& cst [[buffer(2)]],\n" " const device uchar2 *wt [[buffer(3)]],\n" @@ -1938,7 +1967,7 @@ const char* shader_MetalConvolution1x1_metal = " }\n" " }\n" "}\n" -"kernel void conv1x1_gemm_16x32_w4(const device M4 *in [[buffer(0)]],\n" +"kernel void conv1x1_gemm_16x32_w4_sg(const device M4 *in [[buffer(0)]],\n" " device M4 *out [[buffer(1)]],\n" " constant conv1x1_constants& cst [[buffer(2)]],\n" " const device uchar2 *wt [[buffer(3)]],\n" @@ -2041,7 +2070,7 @@ const char* shader_MetalConvolution1x1_metal = " }\n" " }\n" "}\n" -"kernel void conv1x1_gemm_32x64_w4(const device M2 *in [[buffer(0)]],\n" +"kernel void conv1x1_gemm_32x64_w4_sg(const device M2 *in [[buffer(0)]],\n" " device M4 *out [[buffer(1)]],\n" " constant conv1x1_constants& cst [[buffer(2)]],\n" " const device uchar2 *wt [[buffer(3)]],\n" @@ -2219,7 +2248,7 @@ const char* shader_MetalConvolution1x1_metal = " if (computeSize>2) {xy_out[2]=activate(M4(result2),cst.activation); }\n" " if (computeSize>3) {xy_out[3]=activate(M4(result3),cst.activation); }\n" "}\n" -"kernel void conv1x1_gemv_g8_w4(const device M4 *in [[buffer(0)]],\n" +"kernel void conv1x1_gemv_g8_w4_sg(const device M4 *in [[buffer(0)]],\n" " device M4 *out [[buffer(1)]],\n" " constant conv1x1_constants& cst [[buffer(2)]],\n" " const device MNN::uchar4x2 *wt [[buffer(3)]],\n" @@ -2272,7 +2301,7 @@ const char* shader_MetalConvolution1x1_metal = " xy_out[0]=activate(M4(res+biasValue),cst.activation);\n" " }\n" "}\n" -"kernel void conv1x1_gemv_g16_w4(const device M4 *in [[buffer(0)]],\n" +"kernel void conv1x1_gemv_g16_w4_sg(const device M4 *in [[buffer(0)]],\n" " device M4 *out [[buffer(1)]],\n" " constant conv1x1_constants& cst [[buffer(2)]],\n" " const device MNN::uchar4x2 *wt [[buffer(3)]],\n" @@ -2556,7 +2585,7 @@ const char* shader_MetalConvolution1x1_metal = " if (widthSize>3) {xy_out[cst.output_size*cst.batch +3]=activate(M4(result7),cst.activation); }\n" " }\n" "}\n" -"kernel void conv1x1_gemm_16x16(const device M4 *in [[buffer(0)]],\n" +"kernel void conv1x1_gemm_16x16_sg(const device M4 *in [[buffer(0)]],\n" " device M4 *out [[buffer(1)]],\n" " constant conv1x1_constants& cst [[buffer(2)]],\n" " const device M4 *wt [[buffer(3)]],\n" @@ -2619,7 +2648,7 @@ const char* shader_MetalConvolution1x1_metal = " }\n" " }\n" "}\n" -"kernel void conv1x1_gemm_32x16(const device M4 *in [[buffer(0)]],\n" +"kernel void conv1x1_gemm_32x16_sg(const device M4 *in [[buffer(0)]],\n" " device M4 *out [[buffer(1)]],\n" " constant conv1x1_constants& cst [[buffer(2)]],\n" " const device M4 *wt [[buffer(3)]],\n" diff --git a/source/backend/metal/MetalBackend.hpp b/source/backend/metal/MetalBackend.hpp index 88996a968..1e6135a1c 100644 --- a/source/backend/metal/MetalBackend.hpp +++ b/source/backend/metal/MetalBackend.hpp @@ -71,7 +71,7 @@ class MetalRuntime : public Runtime { virtual std::pair onGetCache() override; virtual bool onSetCache(const void* buffer, size_t size) override; - static MetalRuntime* create(const Backend::Info& info, id device); + static MetalRuntime* create(const Backend::Info& info); virtual void onMaskOpReady(const std::vector& inputs, const std::vector& outputs, const MNN::Op* op) override; virtual bool onMeasure(const std::vector& inputs, const std::vector& outputs, @@ -160,8 +160,11 @@ class MetalBackend : public Backend { void returnConstBuffer(id buffer) const; id makeComputePipelineWithSourceOption(const char* csource, const char* cname, MTLCompileOptions *options) const; public: - MetalBackend(std::shared_ptr staticMem, const MetalRuntime* runtime, bool usefp16AsFp32); + MetalBackend(std::shared_ptr staticMem, const MetalRuntime* runtime, bool usefp16AsFp32, BackendConfig::MemoryMode mode); virtual ~MetalBackend(); + virtual Runtime* getRuntime() override { + return (Runtime*)mRuntime; + } const MetalRuntime* runtime() const { return mRuntime; } @@ -224,6 +227,11 @@ class MetalBackend : public Backend { MTLSize localSize; MTLSize groupSize; }; + BackendConfig::MemoryMode getMemoryMode() const { + return mMemoryMode; + } +private: + BackendConfig::MemoryMode mMemoryMode; private: MetalRuntimeAllocator::MetalBufferAlloc mEmptyMem; id getCommandBufferForBufferCopy() const; diff --git a/source/backend/metal/MetalBackend.mm b/source/backend/metal/MetalBackend.mm index d0d5229a2..649c75b34 100644 --- a/source/backend/metal/MetalBackend.mm +++ b/source/backend/metal/MetalBackend.mm @@ -12,6 +12,7 @@ #define METAL_CONST_BUFFER_LIMIT 128 #define METAL_SEPERATE_MAX_COUNT 2 #if MNN_METAL_ENABLED +#include #import "backend/metal/MNNMetalContext.h" #import "core/Macro.h" #import "core/TensorUtils.hpp" @@ -70,7 +71,7 @@ static void _MetalApplyTensor(uint8_t* host, size_t offset, Tensor* t) { map->insert(std::make_pair(t, c)); } -MetalBackend::MetalBackend(std::shared_ptr staticMem, const MetalRuntime* runtime, bool usefp16AsFp32) : Backend(MNN_FORWARD_METAL), +MetalBackend::MetalBackend(std::shared_ptr staticMem, const MetalRuntime* runtime, bool usefp16AsFp32, BackendConfig::MemoryMode mode) : Backend(MNN_FORWARD_METAL), mEmptyMem(nil) { mRuntime = runtime; @@ -79,6 +80,7 @@ static void _MetalApplyTensor(uint8_t* host, size_t offset, Tensor* t) { mCurrentAllocator = mBufferPool.get(); mStaticBufferPool = staticMem; mUseFloatAsFp16 = usefp16AsFp32; + mMemoryMode = mode; mIsIphone = ctx.isIphone; if (runtime->getCommandQueue() == nil) { // one command queue can create only a few command buffer, so let each backend own a command queue @@ -191,6 +193,9 @@ MemChunk chunk() override { buffer = mCurrentAllocator->alloc(size, true); allocator = mCurrentAllocator; } break; + default:{ + break; + } } if (storageType == Backend::STATIC) { if(nullptr == buffer.first) { @@ -928,7 +933,14 @@ static void _execute(id encoder, const MetalBackend::C } } -MetalRuntime* MetalRuntime::create(const Backend::Info& info, id device) { +struct MetalContext { + std::mutex pLock; + MNNMetalContext* pContext; + id pDevice; +}; +static MetalContext* gContext = nullptr; +MetalRuntime* MetalRuntime::create(const Backend::Info& info) { + std::unique_lock _l(gContext->pLock); MNNMetalSharedContext sharedContext; sharedContext.device = nil; sharedContext.queue = nil; @@ -939,15 +951,18 @@ static void _execute(id encoder, const MetalBackend::C } } if (nil == sharedContext.device) { - sharedContext.device = device; - } - auto mContext = (__bridge_retained void *)[[MNNMetalContext alloc] init]; - auto ctx = (__bridge MNNMetalContext *)mContext; - BOOL res = [ctx initWithSharedContext:&sharedContext dev:device]; - if (!res) { - CFRelease(mContext); - return nullptr; + sharedContext.device = MTLCreateSystemDefaultDevice(); + } + if (nil == gContext->pContext || gContext->pDevice != sharedContext.device) { + gContext->pContext = [[MNNMetalContext alloc] init]; + gContext->pDevice = sharedContext.device; + BOOL res = [gContext->pContext initWithSharedContext:&sharedContext dev:sharedContext.device]; + if (!res) { + gContext->pContext = nil; + return nullptr; + } } + auto mContext = (__bridge_retained void *)(gContext->pContext); auto rt = new MetalRuntime(mContext); rt->setGpuMode(info.gpuMode); if (nil != sharedContext.queue) { @@ -1175,17 +1190,19 @@ virtual void onRelease(MemChunk chunk) override { Backend* MetalRuntime::onCreate(const BackendConfig* config, Backend* origin) const { if (hint().weightMemoryPath.size() > 0 && mStaticCache.get() == nullptr) { auto ctx = (__bridge MNNMetalContext *)mContext; - auto mmap = BufferAllocator::Allocator::createMmap(hint().weightMemoryPath.c_str(), "metal.weight"); + auto mmap = BufferAllocator::Allocator::createMmap(hint().weightMemoryPath.c_str(), "", "metal.weight"); std::shared_ptr mmapMem(new MetalWrapAllocator(mmap, [ctx device])); mStaticCache = mStatic; mStatic.reset(new EagerBufferAllocator(mmapMem, 32, 1024 * 1024 * 1024)); } BackendConfig::PrecisionMode precision = mDefaultConfig.precision; + BackendConfig::MemoryMode memory = mDefaultConfig.memory; if (nullptr != config) { precision = config->precision; + memory = config->memory; } bool useFp16AsFp32 = precision != BackendConfig::Precision_High; - return new MetalBackend(mStatic, this, useFp16AsFp32); + return new MetalBackend(mStatic, this, useFp16AsFp32, memory); } void MetalRuntime::onGabageCollect(int level) { @@ -1231,14 +1248,14 @@ virtual void onRelease(MemChunk chunk) override { class MetalRuntimeCreator : public RuntimeCreator { public: - MetalRuntimeCreator(id device) { - mDevice = device; + MetalRuntimeCreator() { + // Do nothing } virtual ~ MetalRuntimeCreator() { // Do nothing } virtual Runtime *onCreate(const Backend::Info &info) const { - auto rt = MetalRuntime::create(info, mDevice); + auto rt = MetalRuntime::create(info); return rt; } private: @@ -1251,11 +1268,14 @@ void registerMetalRuntimeCreator() { // not all device with iOS 8+ supports metal. id device = MTLCreateSystemDefaultDevice(); if (nil != device) { + gContext = new MetalContext; + gContext->pContext = nil; + gContext->pDevice = nil; registerMetalOps(); #ifdef MNN_SUPPORT_RENDER registerMetalRenderOps(); #endif - MNNInsertExtraRuntimeCreator(MNN_FORWARD_METAL, new MetalRuntimeCreator(device), false); + MNNInsertExtraRuntimeCreator(MNN_FORWARD_METAL, new MetalRuntimeCreator, false); } else { MNN_ERROR("Init Metal Error\n"); } diff --git a/source/backend/metal/MetalConvolution1x1.mm b/source/backend/metal/MetalConvolution1x1.mm index 1d0c8d7c4..7bdf0a893 100644 --- a/source/backend/metal/MetalConvolution1x1.mm +++ b/source/backend/metal/MetalConvolution1x1.mm @@ -25,8 +25,10 @@ MetalConvolution1x1::MetalConvolution1x1(Backend *backend, const MNN::Op *op) : MetalConvolutionCommon(backend, op, nullptr) { auto conv2D = op->main_as_Convolution2D(); bool ldInt8Weight = false; - if (conv2D->quanParameter() && (conv2D->external() || conv2D->quanParameter()->buffer())) { - ldInt8Weight = true; + if(static_cast(backend)->getMemoryMode() == BackendConfig::Memory_Low) { + if (conv2D->quanParameter() && (conv2D->external() || conv2D->quanParameter()->buffer())) { + ldInt8Weight = true; + } } loadWeight(op, ldInt8Weight); } @@ -105,13 +107,12 @@ if(rt->supportSimdGroupReduce() && ob * ow * oh == 1) { // unrool c for avoid memory exceed if(oc > 16384 && oc_4 % 2 == 0) { - mPipeline = [context pipelineWithName:@"conv1x1_gemv_g16_w4" fp16:backend->useFp16InsteadFp32()]; - name = "conv1x1_gemv_g16_w4"; + mPipeline = [context pipelineWithName:@"conv1x1_gemv_g16_w4_sg" fp16:backend->useFp16InsteadFp32()]; + // MNN_PRINT("g16 ic: %d oc: %d\n", input->channel(), oc); mThreads = std::make_pair(MTLSizeMake(UP_DIV(oc, 16), 1, 1), MTLSizeMake(64, 1, 1)); } else { - mPipeline = [context pipelineWithName:@"conv1x1_gemv_g8_w4" fp16:backend->useFp16InsteadFp32()]; - name = "conv1x1_gemv_g8_w4"; + mPipeline = [context pipelineWithName:@"conv1x1_gemv_g8_w4_sg" fp16:backend->useFp16InsteadFp32()]; // MNN_PRINT("g8 ic: %d oc: %d\n", input->channel(), oc); mThreads = std::make_pair(MTLSizeMake(UP_DIV(oc, 8), 1, 1), MTLSizeMake(64, 1, 1)); } @@ -121,21 +122,17 @@ auto smem_size = [[context device] maxThreadgroupMemoryLength]; // choose different tile for different computation if(ob * ow * oh >= 128 && oc >= 512 && ob * ow * oh * oc > 512 * 2048 && smem_size >= 8192) { - mPipeline = [context pipelineWithName:@"conv1x1_gemm_32x64_w4" fp16:backend->useFp16InsteadFp32()]; - name = "conv1x1_gemm_32x64_w4"; + mPipeline = [context pipelineWithName:@"conv1x1_gemm_32x64_w4_sg" fp16:backend->useFp16InsteadFp32()]; mThreads = std::make_pair(MTLSizeMake(UP_DIV(ob * ow * oh, 32), UP_DIV(oc, 64), 1), MTLSizeMake(128, 1, 1)); } else if(ob * ow * oh >= 32 && ob * ow * oh * oc > 128 * 2048) { - mPipeline = [context pipelineWithName:@"conv1x1_gemm_32x16_w4" fp16:backend->useFp16InsteadFp32()]; - name = "conv1x1_gemm_32x16_w4"; + mPipeline = [context pipelineWithName:@"conv1x1_gemm_32x16_w4_sg" fp16:backend->useFp16InsteadFp32()]; mThreads = std::make_pair(MTLSizeMake(UP_DIV(ob * ow * oh, 32), UP_DIV(oc, 16), 1), MTLSizeMake(32, 1, 1)); } else if(oc > 512 && ob * ow * oh * oc > 128 * 2048) { - mPipeline = [context pipelineWithName:@"conv1x1_gemm_16x32_w4" fp16:backend->useFp16InsteadFp32()]; - name = "conv1x1_gemm_16x32_w4"; + mPipeline = [context pipelineWithName:@"conv1x1_gemm_16x32_w4_sg" fp16:backend->useFp16InsteadFp32()]; mThreads = std::make_pair(MTLSizeMake(UP_DIV(ob * ow * oh, 16), UP_DIV(oc, 32), 1), MTLSizeMake(32, 1, 1)); } else { - mPipeline = [context pipelineWithName:@"conv1x1_gemm_16x16_w4" fp16:backend->useFp16InsteadFp32()]; - name = "conv1x1_gemm_16x16_w4"; + mPipeline = [context pipelineWithName:@"conv1x1_gemm_16x16_w4_sg" fp16:backend->useFp16InsteadFp32()]; // MNN_PRINT("gemm M: %d N: %d\n", ob * ow * oh, oc); mThreads = std::make_pair(MTLSizeMake(UP_DIV(ob * ow * oh, 16), UP_DIV(oc, 16), 1), MTLSizeMake(32, 1, 1)); } @@ -173,16 +170,25 @@ if(ob * ow * oh >= 16 && ic_4 >= 4 && ic_4 % 2 == 0 && oc_4 >= 4 && ob * ow * oh * ic_4 * oc_4 >= 64 * 64 * 64) { // Enough threads if(ob * ow * oh * oc_4 / ic_4 >= 1024) { - mPipeline = [context pipelineWithName:@"conv1x1_gemm_32x16" fp16:backend->useFp16InsteadFp32()]; + mPipeline = [context pipelineWithName:@"conv1x1_gemm_32x16_sg" fp16:backend->useFp16InsteadFp32()]; mThreads = std::make_pair(MTLSizeMake(UP_DIV(ob * ow * oh, 32), UP_DIV(oc, 16), 1), MTLSizeMake(32, 1, 1)); } else { - mPipeline = [context pipelineWithName:@"conv1x1_gemm_16x16" fp16:backend->useFp16InsteadFp32()]; + mPipeline = [context pipelineWithName:@"conv1x1_gemm_16x16_sg" fp16:backend->useFp16InsteadFp32()]; mThreads = std::make_pair(MTLSizeMake(UP_DIV(ob * ow * oh, 16), UP_DIV(oc, 16), 1), MTLSizeMake(32, 1, 1)); } return NO_ERROR; } } - + if(rt->supportSimdGroupReduce()) { + // do input_channel reduce + auto magic_num = 4.0; // total threads pretty small and loop pretty large + if(ic_4 >= 32 && ic_4 % 2 == 0 && 1.0 * ob * ow * oh * oc_4 / ic_4 < magic_num) { + mPipeline = [context pipelineWithName:@"conv1x1_z4_sg" fp16:backend->useFp16InsteadFp32()]; + mThreads = std::make_pair(MTLSizeMake(ow * oh, oc_4, ob), MTLSizeMake(32, 1, 1)); + return NO_ERROR; + } + } +// printf("lora: %d %d %d %d %d\n", ob, oh, ow, oc, input->channel()); if(rt->getTuneLevel() == Never) { if (ow * oh >= 128) { NSUInteger gid_x = UP_DIV(ow * oh, 8); diff --git a/source/backend/metal/shader/MetalConvolution1x1.metal b/source/backend/metal/shader/MetalConvolution1x1.metal index 07ac77b3e..090b57415 100644 --- a/source/backend/metal/shader/MetalConvolution1x1.metal +++ b/source/backend/metal/shader/MetalConvolution1x1.metal @@ -72,6 +72,37 @@ kernel void conv1x1_g1z4(const device ftype4 *in [[buffer(0)]], if (computeSize > 3) {xy_out[3] = activate(ftype4(result3), cst.activation); } } +kernel void conv1x1_z4_sg(const device ftype4 *in [[buffer(0)]], + device ftype4 *out [[buffer(1)]], + constant conv1x1_constants& cst [[buffer(2)]], + const device ftype4x4 *wt [[buffer(3)]], + const device ftype4 *biasTerms [[buffer(4)]], + uint3 gid[[threadgroup_position_in_grid]], + uint tiisg[[thread_index_in_simdgroup]], + uint sgitg[[simdgroup_index_in_threadgroup]]) { + if ((int)gid.x >= cst.output_size || (int)gid.y >= cst.output_slice || (int)gid.z >= cst.batch) return; + + int rx = gid.x; + int uz = gid.y; + auto xy_wt = wt + uz * cst.input_slice; + auto xy_in0 = in + (int)gid.z * cst.input_size + rx + 0; + auto xy_out = out + (int)gid.z * cst.output_size + uz * cst.output_size * cst.batch + rx; + auto biasValue = FLOAT4(biasTerms[uz]); + FLOAT4 result0 = 0; + int computeSize = min(cst.output_size - rx, CONV_UNROLL); + + for (auto z = tiisg; z < cst.input_slice; z+SIMD_GROUP_WIDTH) { + auto in40 = *xy_in0; + auto w = xy_wt[z]; + + result0 += FLOAT4(in40 * w); + xy_in0 += cst.input_size * cst.batch; + } + result0 = simd_sum(result0); + + *xy_out = activate(ftype4(result0 + biasValue), cst.activation); +} + kernel void conv1x1_g1z4_w8(const device ftype4 *in [[buffer(0)]], device ftype4 *out [[buffer(1)]], constant conv1x1_constants& cst [[buffer(2)]], @@ -123,7 +154,7 @@ kernel void conv1x1_g1z4_w8(const device ftype4 *in [[buffer(0)]], } -kernel void conv1x1_gemm_16x16_w4(const device ftype4 *in [[buffer(0)]], +kernel void conv1x1_gemm_16x16_w4_sg(const device ftype4 *in [[buffer(0)]], device ftype4 *out [[buffer(1)]], constant conv1x1_constants& cst [[buffer(2)]], const device uchar2 *wt [[buffer(3)]], @@ -216,7 +247,7 @@ kernel void conv1x1_gemm_16x16_w4(const device ftype4 *in [[buffer(0) } } -kernel void conv1x1_gemm_32x16_w4(const device ftype4 *in [[buffer(0)]], +kernel void conv1x1_gemm_32x16_w4_sg(const device ftype4 *in [[buffer(0)]], device ftype4 *out [[buffer(1)]], constant conv1x1_constants& cst [[buffer(2)]], const device uchar2 *wt [[buffer(3)]], @@ -320,7 +351,7 @@ kernel void conv1x1_gemm_32x16_w4(const device ftype4 *in [[buffer(0) } } -kernel void conv1x1_gemm_16x32_w4(const device ftype4 *in [[buffer(0)]], +kernel void conv1x1_gemm_16x32_w4_sg(const device ftype4 *in [[buffer(0)]], device ftype4 *out [[buffer(1)]], constant conv1x1_constants& cst [[buffer(2)]], const device uchar2 *wt [[buffer(3)]], @@ -430,7 +461,7 @@ kernel void conv1x1_gemm_16x32_w4(const device ftype4 *in [[buffer(0) } -kernel void conv1x1_gemm_32x64_w4(const device ftype2 *in [[buffer(0)]], +kernel void conv1x1_gemm_32x64_w4_sg(const device ftype2 *in [[buffer(0)]], device ftype4 *out [[buffer(1)]], constant conv1x1_constants& cst [[buffer(2)]], const device uchar2 *wt [[buffer(3)]], @@ -617,7 +648,7 @@ kernel void conv1x1_g1z4_w4(const device ftype4 *in [[buffer(0)]], if (computeSize > 3) {xy_out[3] = activate(ftype4(result3), cst.activation); } } -kernel void conv1x1_gemv_g8_w4(const device ftype4 *in [[buffer(0)]], +kernel void conv1x1_gemv_g8_w4_sg(const device ftype4 *in [[buffer(0)]], device ftype4 *out [[buffer(1)]], constant conv1x1_constants& cst [[buffer(2)]], const device MNN::uchar4x2 *wt [[buffer(3)]], @@ -679,7 +710,7 @@ kernel void conv1x1_gemv_g8_w4(const device ftype4 *in [[buffer(0)]], -kernel void conv1x1_gemv_g16_w4(const device ftype4 *in [[buffer(0)]], +kernel void conv1x1_gemv_g16_w4_sg(const device ftype4 *in [[buffer(0)]], device ftype4 *out [[buffer(1)]], constant conv1x1_constants& cst [[buffer(2)]], const device MNN::uchar4x2 *wt [[buffer(3)]], @@ -1004,7 +1035,7 @@ kernel void conv1x1_w4c2(const device ftype4 *in [[buffer(0)]], } } -kernel void conv1x1_gemm_16x16(const device ftype4 *in [[buffer(0)]], +kernel void conv1x1_gemm_16x16_sg(const device ftype4 *in [[buffer(0)]], device ftype4 *out [[buffer(1)]], constant conv1x1_constants& cst [[buffer(2)]], const device ftype4 *wt [[buffer(3)]], @@ -1072,7 +1103,7 @@ kernel void conv1x1_gemm_16x16(const device ftype4 *in [[buffer(0)]], } -kernel void conv1x1_gemm_32x16(const device ftype4 *in [[buffer(0)]], +kernel void conv1x1_gemm_32x16_sg(const device ftype4 *in [[buffer(0)]], device ftype4 *out [[buffer(1)]], constant conv1x1_constants& cst [[buffer(2)]], const device ftype4 *wt [[buffer(3)]], diff --git a/source/backend/opencl/core/BufferPool.cpp b/source/backend/opencl/core/BufferPool.cpp index 4398d4bd1..f78037d13 100644 --- a/source/backend/opencl/core/BufferPool.cpp +++ b/source/backend/opencl/core/BufferPool.cpp @@ -18,7 +18,7 @@ cl::Buffer* BufferPool::alloc(size_t size, bool separate) { return buffer; } } - std::shared_ptr node(new Node); + std::shared_ptr node(new OpenCLBufferNode); cl_int ret = CL_SUCCESS; mTotalSize += size; node->size = size; @@ -59,5 +59,71 @@ void BufferPool::releaseFreeList() { } mFreeList.clear(); } + +std::shared_ptr BufferExecutionPool::alloc(size_t size, bool separate) { + if (!separate) { + auto iter = mFreeList.lower_bound(size); + if (iter != mFreeList.end()) { + auto node = iter->second; + mFreeList.erase(iter); + return node; + } else if(mFreeList.size() != 0){ + cl_int ret = CL_SUCCESS; + // Synchronize to prevent old buffer references + mCommand.finish(); + auto maxIter = mFreeList.rbegin(); + auto node = maxIter->second; + mTotalSize += size - node.get()->size; + node.get()->size = size; + node.get()->buffer.reset(new cl::Buffer(mContext, mFlag, size, NULL, &ret)); + if (nullptr == node.get()->buffer.get() || ret != CL_SUCCESS) { + MNN_ERROR("Alloc Buffer %lu error, code:%d \n", size, ret); + return nullptr; + } + mFreeList.erase(std::prev(mFreeList.end())); + return node; + } + } + std::shared_ptr node(new OpenCLBufferNode); + cl_int ret = CL_SUCCESS; + mTotalSize += size; + node->size = size; + node->buffer.reset(new cl::Buffer(mContext, mFlag, size, NULL, &ret)); + if (nullptr == node->buffer.get() || ret != CL_SUCCESS) { + MNN_ERROR("Alloc Buffer %lu error, code:%d \n", size, ret); + return nullptr; + } + mAllBuffer.insert(node); + return node; +} + +void BufferExecutionPool::recycle(std::shared_ptr node, bool release) { + auto iter = mAllBuffer.find(node); + if (iter == mAllBuffer.end()) { + MNN_ERROR("Error for recycle buffer\n"); + return; + } + if (release) { + mAllBuffer.erase(node); + return; + } + mFreeList.insert(std::make_pair(node.get()->size, node)); +} + +void BufferExecutionPool::clear() { + mFreeList.clear(); + mAllBuffer.clear(); + mTotalSize = 0; +} + +void BufferExecutionPool::releaseFreeList() { + for(auto mf : mFreeList){ + auto iter = mAllBuffer.find(mf.second); + if (iter != mAllBuffer.end()) { + mAllBuffer.erase(iter); + } + } + mFreeList.clear(); +} } // namespace OpenCL } // namespace MNN diff --git a/source/backend/opencl/core/BufferPool.hpp b/source/backend/opencl/core/BufferPool.hpp index b9acd5370..021789b11 100644 --- a/source/backend/opencl/core/BufferPool.hpp +++ b/source/backend/opencl/core/BufferPool.hpp @@ -9,6 +9,7 @@ #ifndef BufferPool_hpp #define BufferPool_hpp +#include #include #include #include @@ -17,6 +18,12 @@ namespace MNN { namespace OpenCL { +struct OpenCLBufferNode{ + OpenCLBufferNode(){}; + size_t size; + std::shared_ptr buffer; +}; + class BufferPool : public NonCopyable { public: BufferPool(cl::Context& context, cl_mem_flags flags) : mContext(context) { @@ -29,16 +36,32 @@ class BufferPool : public NonCopyable { void releaseFreeList(); size_t totalSize() { return mTotalSize; } - struct Node { - size_t size; - std::shared_ptr buffer; - }; +private: + std::map> mAllBuffer; + std::multimap> mFreeList; + + cl::Context& mContext; + cl_mem_flags mFlag; + size_t mTotalSize = 0; +}; +class BufferExecutionPool : public NonCopyable { +public: + BufferExecutionPool(cl::Context& context, cl::CommandQueue& command, cl_mem_flags flags) : mContext(context), mCommand(command) { + mFlag = flags; + } + + std::shared_ptr alloc(size_t size, bool separate = false); + void recycle(std::shared_ptr node, bool release = false); + void clear(); + void releaseFreeList(); + size_t totalSize() { return mTotalSize; } private: - std::map> mAllBuffer; - std::multimap> mFreeList; + std::set> mAllBuffer; + std::multimap> mFreeList; cl::Context& mContext; + cl::CommandQueue& mCommand; cl_mem_flags mFlag; size_t mTotalSize = 0; }; diff --git a/source/backend/opencl/core/OpenCLBackend.cpp b/source/backend/opencl/core/OpenCLBackend.cpp index 8b478ec57..cf87faa6c 100644 --- a/source/backend/opencl/core/OpenCLBackend.cpp +++ b/source/backend/opencl/core/OpenCLBackend.cpp @@ -239,6 +239,7 @@ OpenCLBackend::OpenCLBackend(BackendConfig::PrecisionMode precision, BackendConf mImagePoolFirst.reset(new ImagePool(mOpenCLRuntime->context())); mBufferPoolFirst.reset(new BufferPool(mOpenCLRuntime->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR)); + mExecutionBufferPool.reset(new BufferExecutionPool(mOpenCLRuntime->context(), mOpenCLRuntime->commandQueue(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR)); mImagePool = mImagePoolFirst.get(); mBufferPool = mBufferPoolFirst.get(); } @@ -256,6 +257,7 @@ OpenCLBackend::~OpenCLBackend() { mRecordings.clear(); mImagePool = nullptr; mBufferPool = nullptr; + mExecutionBufferPool->clear(); if(mMapMem.second != nullptr) { #ifdef MNN_OPENCL_SVM_ENABLE if(mUseSvm) @@ -275,6 +277,20 @@ OpenCLRuntime* OpenCLBackend::getOpenCLRuntime() { return mOpenCLRuntime.get(); } +class CLReleaseExecutionBuffer : public Backend::MemObj { +public: + CLReleaseExecutionBuffer(std::shared_ptr node, BufferExecutionPool* bufferPool) { + mNode = node; + mBufferPool = bufferPool; + } + virtual ~ CLReleaseExecutionBuffer() { + mBufferPool->recycle(mNode); + } +private: + std::shared_ptr mNode; + BufferExecutionPool* mBufferPool; +}; + class CLMemReleaseBuffer : public Backend::MemObj { public: CLMemReleaseBuffer(cl::Buffer* bId, BufferPool* bufferPool) { @@ -369,6 +385,11 @@ Backend::MemObj* OpenCLBackend::onAcquire(const Tensor* nativeTensor, StorageTyp ((Tensor*)nativeTensor)->buffer().device = (uint64_t)buffer; return new CLMemReleaseBuffer(buffer, mBufferPool); } + if (storageType == DYNAMIC_IN_EXECUTION){ + auto node = mExecutionBufferPool->alloc(size*typeSize); + ((Tensor*)nativeTensor)->buffer().device = reinterpret_cast(node.get()); + return new CLReleaseExecutionBuffer(node, mExecutionBufferPool.get()); + } MNN_ASSERT(storageType == STATIC); auto buffer = mStaticBufferPool->alloc(size*typeSize); diff --git a/source/backend/opencl/core/OpenCLBackend.hpp b/source/backend/opencl/core/OpenCLBackend.hpp index caf80b792..fd2b732ef 100644 --- a/source/backend/opencl/core/OpenCLBackend.hpp +++ b/source/backend/opencl/core/OpenCLBackend.hpp @@ -162,6 +162,7 @@ class OpenCLBackend : public Backend { ImagePool* mImagePool; BufferPool* mBufferPool; + std::shared_ptr mExecutionBufferPool; std::shared_ptr mImagePoolFirst; std::shared_ptr mBufferPoolFirst; diff --git a/source/backend/opencl/core/OpenCLGemmTune.cpp b/source/backend/opencl/core/OpenCLGemmTune.cpp index 8f1b63c50..90a0d7400 100644 --- a/source/backend/opencl/core/OpenCLGemmTune.cpp +++ b/source/backend/opencl/core/OpenCLGemmTune.cpp @@ -203,11 +203,34 @@ std::vector getGemmParams(const std::vector &gemmSize, const if (tunedGemmParams.find(info) != tunedGemmParams.end()) { return tunedGemmParams[info]; } + + // top gpu device and large computation + if(runtime->getGpuLevel() == TOP && (runtime->getCLTuneLevel() == None || runtime->getCLTuneLevel() == Fast)) { + // total computation + auto compute_ratio = 1.0 * gemmSize[4] * gemmSize[0] / 1024.0 * gemmSize[1] / 1024.0 * gemmSize[2] / 1024.0; + auto thread_ratio = 1.0 * gemmSize[4] * gemmSize[0] / 1024.0 * gemmSize[1] / 1024.0; + + // each dimension is even + bool is_even = gemmSize[0] >= 512 && gemmSize[1] >= 256; + bool is_div = gemmSize[0] % 128 == 0 && gemmSize[1] % 128 == 0; + if(compute_ratio >= 2.0 && thread_ratio >= 2.0 && is_even && is_div) { + return {16, 2, 16, 16, 128, 16, 16, 128, 0, 0, 0, 0, 8, 8}; + } + } std::vector tuneLwsRes; if(GemmlocalWSTune(tuneLws, gemmSize, tuneLwsRes, runtime)){ return tuneLwsRes; } + std::vector params_prefer = {16, 2, 4, 4, 16, 4, 4, 16, 0, 0, 1, 0, 2, 2}; + + auto thread_ratio = 1.0 * gemmSize[4] * gemmSize[0] / 512.0 * gemmSize[1] / 512.0; + bool is_div = gemmSize[0] % 64 == 0 && gemmSize[1] % 32 == 0; + // init params with pretty suitable candidate to avoid to slow initial + if(thread_ratio >= 1.0 && is_div) { + params_prefer.assign({16, 2, 16, 16, 64 , 8 , 8 , 32 , 0, 0, 0, 0, 4, 4}); + } + if(runtime->getCLTuneLevel() == None) { auto getMaxDivisor = [](uint32_t num) -> uint32_t { std::vector divisors = {128, 64, 32}; @@ -240,11 +263,10 @@ std::vector getGemmParams(const std::vector &gemmSize, const return {16, 2, 8, 8, 64, 8, 8, 64, 0, 0, 1, 0, 4, 4}; } } - return {16, 2, 4, 4, 16, 4, 4, 16, 0, 0, 1, 0, 2, 2}; + return params_prefer; } std::vector> totalCombinations; // save total candidate combinations - std::vector params_prefer = {16, 2, 4, 4, 16, 4, 4, 16, 0, 0, 1, 0, 2, 2}; totalCombinations.emplace_back(params_prefer); uint32_t min_cost = UINT_MAX; @@ -257,7 +279,6 @@ std::vector getGemmParams(const std::vector &gemmSize, const totalCombinations.push_back({16, 2, 8 , 8 , 16 , 8 , 8 , 64, 0, 0, 0, 0, 2, 8}); totalCombinations.push_back({16, 2, 16, 16, 64 , 8 , 8 , 128, 0, 0, 0, 1, 4, 8});//10 - totalCombinations.push_back({16, 2, 16, 16, 64 , 8 , 8 , 32 , 0, 0, 0, 0, 4, 4}); totalCombinations.push_back({16, 2, 8, 8 , 32 , 8 , 8 , 128, 0, 0, 1, 0, 2, 8});//2 totalCombinations.push_back({16, 2, 16, 16, 64 , 8 , 8 , 128, 0, 0, 1, 1, 2, 8});//12 totalCombinations.push_back({16, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 1, 2, 8});//2 @@ -416,6 +437,8 @@ std::vector getGemmParams(const std::vector &gemmSize, const int batch_offset_b = gemmSize[1] * gemmSize[2]; int batch_offset_c = gemmSize[0] * gemmSize[1]; int batch_offset[4] = {batch_offset_a, batch_offset_b, batch_offset_c, 0}; + int base_ptr_offset[4] = {0, 0, 0, 0}; + int group[4] = {1, (int)groupSize, 1, (int)gemmSize[4]}; ret |= kernel->get().setArg(idx++, tensorMemory[0]); @@ -425,6 +448,7 @@ std::vector getGemmParams(const std::vector &gemmSize, const } ret |= kernel->get().setArg(idx++, tensorMemory[2]); ret |= kernel->get().setArg(idx++, sizeof(batch_offset), batch_offset); + ret |= kernel->get().setArg(idx++, sizeof(batch_offset), base_ptr_offset); ret |= kernel->get().setArg(idx++, sizeof(stride), stride); ret |= kernel->get().setArg(idx++, sizeof(group), group); diff --git a/source/backend/opencl/core/OpenCLRunningUtils.cpp b/source/backend/opencl/core/OpenCLRunningUtils.cpp index 549d2be10..abce9f5fb 100644 --- a/source/backend/opencl/core/OpenCLRunningUtils.cpp +++ b/source/backend/opencl/core/OpenCLRunningUtils.cpp @@ -152,7 +152,7 @@ std::pair, uint32_t> localWS3DDefault(const std::vector= ALIMIN(16, gws[0]*gws[1]*gws[2] / 100)) { cl::Event event; std::vector internalGlobalWS(3, 1); for (size_t i = 0; i < gws.size(); ++i) { @@ -197,7 +197,16 @@ std::pair, uint32_t> localWS3DDefault(const std::vector(64)) && lws[0]*lws[1]*lws[2] >= 16) { + bool isTune = lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[2] <= maxWorkItemSizes[2] && lws[0]*lws[1]*lws[2] <= ALIMIN(maxWorkGroupSize, static_cast(64)) && lws[0]*lws[1]*lws[2] >= 16; + if(isTune) { + // pretty much thread count + if(gws[0]*gws[1]*gws[2] >= 256 * 256) { + if(lws[0]*lws[1]*lws[2] < 64) { + isTune = false; + } + } + } + if(isTune) { cl::Event event; std::vector internalGlobalWS(3, 1); for (size_t i = 0; i < gws.size(); ++i) { @@ -368,7 +377,7 @@ std::pair, uint32_t> localWS2DDefault(const std::vector= ALIMIN(16, gws[0]*gws[1] / 100)) { cl::Event event; std::vector internalGlobalWS(2, 1); for (size_t i = 0; i < gws.size(); ++i) { @@ -405,7 +414,17 @@ std::pair, uint32_t> localWS2DDefault(const std::vector= 16) { + bool isTune = lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[0]*lws[1] <= ALIMIN(maxWorkGroupSize, static_cast(64)) && lws[0]*lws[1] >= 16; + + if(isTune) { + // pretty much thread count + if(gws[0]*gws[1] >= 256 * 256) { + if(lws[0]*lws[1] < 64) { + isTune = false; + } + } + } + if(isTune) { cl::Event event; std::vector internalGlobalWS(2, 1); for (size_t i = 0; i < gws.size(); ++i) { @@ -473,6 +492,31 @@ std::pair, uint32_t> localWS2DDefault(const std::vector &gws, const std::vector &lws, OpenCLRuntime *runtime, const std::string &kernelName, const std::shared_ptr &mKernelW){ + auto mKernel = mKernelW->get(); + auto& tunedLws = runtime->tunedLwsMap(); + std::pair> info = std::make_pair(kernelName, gws); + if (tunedLws.find(info) != tunedLws.end()) { + return tunedLws[info].second; + } + + cl::Event event; + cl_int res = runtime->commandQueue().enqueueNDRangeKernel(mKernel, cl::NullRange, + cl::NDRange(gws[0], gws[1]), + cl::NDRange(lws[0], lws[1]), + nullptr, &event); + MNN_CHECK_CL_SUCCESS(res, kernelName.c_str()); + if (res != CL_SUCCESS) { + MNN_PRINT("lws tune res %s\n", kernelName.c_str()); + } + + int cost_time = (int)runtime->getCostTime(&event); + if (tunedLws.find(info) == tunedLws.end()) { + tunedLws.insert(std::make_pair(info, std::make_pair(lws, cost_time))); + } + return cost_time; +} + void run3DKernelDefault(const ::std::shared_ptr &kernelw, const std::vector &gws, const std::vector &lws, OpenCLRuntime *runtime, cl::Event* eventPtr) { #ifdef LOG_VERBOSE diff --git a/source/backend/opencl/core/OpenCLRunningUtils.hpp b/source/backend/opencl/core/OpenCLRunningUtils.hpp index f9a911beb..09f442f9a 100644 --- a/source/backend/opencl/core/OpenCLRunningUtils.hpp +++ b/source/backend/opencl/core/OpenCLRunningUtils.hpp @@ -18,6 +18,7 @@ #include "core/TensorUtils.hpp" #include "backend/opencl/core/runtime/OpenCLRuntime.hpp" #include "backend/opencl/core/runtime/OpenCLWrapper.hpp" +#include "backend/opencl/core/BufferPool.hpp" namespace MNN { namespace OpenCL { @@ -96,6 +97,9 @@ inline void IOHW2OIHW(const T *src, T *dst, Dim O, Dim I, Dim H, Dim W) { } } }; +inline cl::Buffer &openCLDeferBuffer(const Tensor *tensor) { + return *(*(OpenCLBufferNode *)(tensor->deviceId())).buffer.get(); +} inline cl::Buffer &openCLBuffer(const Tensor *tensor) { return (*(cl::Buffer *)(tensor->deviceId())); } @@ -123,6 +127,7 @@ std::pair, uint32_t> localWS3DDefault(const std::vector, std::pair, uint32_t>>>> &tuneMap, const std::vector &gws, const std::string &kernelName, std::pair, uint32_t> &res); +uint32_t get2DUseLocalMemTime(const std::vector &gws, const std::vector &lws, OpenCLRuntime *runtime, const std::string &kernelName, const std::shared_ptr &mKernelW); std::pair, uint32_t> localWS2DDefault(const std::vector &gws, const uint32_t maxWorkGroupSize, OpenCLRuntime *runtime, const std::string &kernelName, const std::shared_ptr &mKernel); diff --git a/source/backend/opencl/core/runtime/OpenCLRuntime.cpp b/source/backend/opencl/core/runtime/OpenCLRuntime.cpp index 7f44dcda9..9fc109e59 100644 --- a/source/backend/opencl/core/runtime/OpenCLRuntime.cpp +++ b/source/backend/opencl/core/runtime/OpenCLRuntime.cpp @@ -125,10 +125,14 @@ OpenCLRuntime::OpenCLRuntime(const BackendConfig::PrecisionMode precision, const // if device is QUALCOMM's and version is 2.0 , set spacial optimized param //if Adreno version is less than Adreno512, donot set WorkGroupAttribute option std::string adrenoVersion = deviceVersion.substr(deviceVersion.size()-3); - //printf("Adreno Version:%s\n", adrenoVersion.c_str()); + // MNN_PRINT("Adreno Version:%s %s\n", deviceVersion.c_str(), adrenoVersion.c_str()); if(mCLVersion > 1.99f && adrenoVersion >= "512") { isSetWorkGroupAttribute = true; } + // 8Gen1 and after + if(adrenoVersion >= "730") { + mGpuLevel = TOP; + } } else if (deviceName.find("Mali") != std::string::npos) { mGpuType = MALI; if(maliArMap.find(deviceName) != maliArMap.end()){ @@ -281,14 +285,16 @@ OpenCLRuntime::OpenCLRuntime(const BackendConfig::PrecisionMode precision, const }else{ mIsCreateError = true; + MNN_ASSERT(1 <= gpuDevices.size()); } }else{ mIsCreateError = true; + MNN_ASSERT(platforms.size() > 0); } if (mIsCreateError) { return; } - { + if (mMemType == IMAGE){ // Init info size_t max_height, max_width; res = mFirstGPUDevicePtr->getInfo(CL_DEVICE_IMAGE2D_MAX_HEIGHT, &max_height); diff --git a/source/backend/opencl/core/runtime/OpenCLRuntime.hpp b/source/backend/opencl/core/runtime/OpenCLRuntime.hpp index 05d7dc619..acf7ffb01 100644 --- a/source/backend/opencl/core/runtime/OpenCLRuntime.hpp +++ b/source/backend/opencl/core/runtime/OpenCLRuntime.hpp @@ -40,6 +40,7 @@ namespace MNN { #define CL_KERNEL_WAVE_SIZE_QCOM 0xAA02 enum GpuType { MALI = 0, ADRENO = 1, RADEON = 2, INTEL = 3, OTHER = 4 }; +enum GpuLevel { UNDEFINED = 0, TOP = 1, MEDIUM = 2, LOW = 3 }; enum MaliAr { MIDGARD = 0, BIFROST = 1, VALHALL = 2 }; enum GpuMemObject { AUTO = 0, BUFFER = 1, IMAGE = 2}; enum CLTuneLevel { None = 0, Heavy = 1, Wide = 2, Normal = 3, Fast = 4}; @@ -125,6 +126,9 @@ class OpenCLRuntime { CLTuneLevel getCLTuneLevel() { return mTuneLevel; } + GpuLevel getGpuLevel() { + return mGpuLevel; + } std::string getDeviceName() { return mDeviceName; } @@ -219,6 +223,7 @@ class OpenCLRuntime { bool mIsSupportAHD = false; GpuType mGpuType; MaliAr mMaliAr; + GpuLevel mGpuLevel = UNDEFINED; float mCLVersion = 1.0f; std::vector> mEvents; diff --git a/source/backend/opencl/execution/buffer/AttentionBufExecution.cpp b/source/backend/opencl/execution/buffer/AttentionBufExecution.cpp index 6a435ca7d..2c6f4a237 100644 --- a/source/backend/opencl/execution/buffer/AttentionBufExecution.cpp +++ b/source/backend/opencl/execution/buffer/AttentionBufExecution.cpp @@ -94,43 +94,6 @@ int AttentionBufExecution::getLocalSize(int size, int maxGroupSize){ return local_size; } -void AttentionBufExecution::reallocKVCache() { - mMax_len = ROUND_UP(mKVCacheCLManager->maxLength(), 4); - int numHead = mKVCacheCLManager->numHead(); - mTempQK.reset(Tensor::createDevice({UP_DIV(mMax_len, 4) * numHead * 4})); - mTempSoftMax.reset(Tensor::createDevice({UP_DIV(mMax_len, 4) * numHead * 4})); - mOpenCLBackend->onAcquireBuffer(mTempQK.get(), Backend::STATIC); - mOpenCLBackend->onAcquireBuffer(mTempSoftMax.get(), Backend::STATIC); - // reset memory for args - if(mOpenCLBackend->isUseRecordQueue()){ - mRgUpdateInfo.update_kernel_args[0].arg_value = &(*(mKVCacheCLManager->key()))(); - mQkUpdateInfo.update_kernel_args[1].arg_value = &(*(mKVCacheCLManager->key()))(); - mQkUpdateInfo.update_kernel_args[2].arg_value = &openCLBuffer(mTempQK.get())(); - mSoftMaxUpdateInfo.update_kernel_args[0].arg_value = &openCLBuffer(mTempQK.get())(); - mSoftMaxUpdateInfo.update_kernel_args[1].arg_value = &openCLBuffer(mTempSoftMax.get())(); - mRgVUpdateInfo.update_kernel_args[0].arg_value = &(*(mKVCacheCLManager->value()))(); - mQkvUpdateInfo.update_kernel_args[0].arg_value = &openCLBuffer(mTempSoftMax.get())(); - mQkvUpdateInfo.update_kernel_args[1].arg_value = &(*(mKVCacheCLManager->value()))(); - }else{ - cl_int ret = CL_SUCCESS; - ret |= mKernel_rearrange->get().setArg(4, *mKVCacheCLManager->key()); - ret |= mKernel_rearrange->get().setArg(6, mMax_len); - ret |= mKernel_qk->get().setArg(3, *mKVCacheCLManager->key()); - ret |= mKernel_qk->get().setArg(4, openCLBuffer(mTempQK.get())); - ret |= mKernel_qk->get().setArg(7, mMax_len); - ret |= mKernel_softmax->get().setArg(3, openCLBuffer(mTempQK.get())); - ret |= mKernel_softmax->get().setArg(4, openCLBuffer(mTempSoftMax.get())); - ret |= mKernel_rearrangeV->get().setArg(4, *mKVCacheCLManager->value()); - ret |= mKernel_rearrangeV->get().setArg(6, mMax_len); - ret |= mKernel_qkv->get().setArg(2, openCLBuffer(mTempSoftMax.get())); - ret |= mKernel_qkv->get().setArg(3, *mKVCacheCLManager->value()); - ret |= mKernel_qkv->get().setArg(6, mMax_len); - MNN_CHECK_CL_SUCCESS(ret, "reset memory arg for AttentionBufExecution"); - } - mOpenCLBackend->onReleaseBuffer(mTempQK.get(), Backend::STATIC); - mOpenCLBackend->onReleaseBuffer(mTempSoftMax.get(), Backend::STATIC); -} - ErrorCode AttentionBufExecution::longPrefillResize(const std::vector &inputs, const std::vector &outputs){ auto query = inputs[0]; @@ -345,6 +308,7 @@ ErrorCode AttentionBufExecution::longPrefillResize(const std::vector & int batch_offset_c = e_pack * h_pack; int batch_offset[4] = {batch_offset_a, batch_offset_b, batch_offset_c, 0}; + int base_ptr_offset[4] = {0, 0, 0, 0}; int stride[4] = {e_pack, h_pack, h_pack, h_pack}; int group[4] = {1, group_size, 1, numHead}; @@ -360,6 +324,7 @@ ErrorCode AttentionBufExecution::longPrefillResize(const std::vector & ret |= mKernel_qk->get().setArg(idx++, openCLBuffer(mTempMask.get())); ret |= mKernel_qk->get().setArg(idx++, openCLBuffer(mTempQK.get())); ret |= mKernel_qk->get().setArg(idx++, batch_offset); + ret |= mKernel_qk->get().setArg(idx++, base_ptr_offset); ret |= mKernel_qk->get().setArg(idx++, stride); ret |= mKernel_qk->get().setArg(idx++, group); MNN_CHECK_CL_SUCCESS(ret, "setArg Self-Attention batchmatmul qk Kernel"); @@ -494,6 +459,7 @@ ErrorCode AttentionBufExecution::longPrefillResize(const std::vector & int batch_offset_b = h_pack * l_pack; int batch_offset_c = e_pack * h_pack; int batch_offset[4] = {batch_offset_a, batch_offset_b, batch_offset_c, 0}; + int base_ptr_offset[4] = {0, 0, 0, 0}; int stride[4] = {e_pack, h_pack, e_pack, h_pack}; int group[4] = {1, group_size, 1, numHead}; @@ -508,6 +474,7 @@ ErrorCode AttentionBufExecution::longPrefillResize(const std::vector & ret |= mKernel_qkv->get().setArg(idx++, openCLBuffer(mTempV.get())); ret |= mKernel_qkv->get().setArg(idx++, openCLBuffer(mTempQKV.get())); ret |= mKernel_qkv->get().setArg(idx++, batch_offset); + ret |= mKernel_qkv->get().setArg(idx++, base_ptr_offset); ret |= mKernel_qkv->get().setArg(idx++, stride); ret |= mKernel_qkv->get().setArg(idx++, group); MNN_CHECK_CL_SUCCESS(ret, "setArg Self-Attention batchmatmul qkv Kernel"); @@ -613,19 +580,9 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c mOpenCLBackend->onReleaseBuffer(mTempQ.get(), Backend::DYNAMIC); mOpenCLBackend->onReleaseBuffer(mTempQK.get(), Backend::DYNAMIC); mOpenCLBackend->onReleaseBuffer(mTempSoftMax.get(), Backend::DYNAMIC); - } else { - mKv_seq_len = mKVCacheCLManager->kvLength() + 1; - int maxLength = mKVCacheCLManager->maxLength(); - mTempQK.reset(Tensor::createDevice({UP_DIV(maxLength, 4) * numHead * 4})); - mTempSoftMax.reset(Tensor::createDevice({UP_DIV(maxLength, 4) * numHead * 4})); - mOpenCLBackend->onAcquireBuffer(mTempQK.get(), Backend::DYNAMIC); - mOpenCLBackend->onAcquireBuffer(mTempSoftMax.get(), Backend::DYNAMIC); - mOpenCLBackend->onReleaseBuffer(mTempQK.get(), Backend::DYNAMIC); - mOpenCLBackend->onReleaseBuffer(mTempSoftMax.get(), Backend::DYNAMIC); - } - mMax_len = ROUND_UP(mKVCacheCLManager->maxLength(), 4); - if(false == mIsDecode){ + int past_len = mIsFirstPrefill ? 0 : mask_kvlen - mask_seqlen; + mKeyValueMaxlen = ROUND_UP(mKVCacheCLManager->maxLength(), 4); { // rearrange query std::set buildOption; @@ -675,7 +632,7 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c ret |= mKernel_rearrange->get().setArg(index++, openCLBuffer(key)); ret |= mKernel_rearrange->get().setArg(index++, *mKVCacheCLManager->key()); ret |= mKernel_rearrange->get().setArg(index++, past_len); - ret |= mKernel_rearrange->get().setArg(index++, mMax_len); + ret |= mKernel_rearrange->get().setArg(index++, mKeyValueMaxlen); ret |= mKernel_rearrange->get().setArg(index++, seq_len); ret |= mKernel_rearrange->get().setArg(index++, kvNumHead); ret |= mKernel_rearrange->get().setArg(index++, numHead); @@ -711,7 +668,7 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c ret |= mKernel_qk->get().setArg(index++, scale); ret |= mKernel_qk->get().setArg(index++, seq_len); ret |= mKernel_qk->get().setArg(index++, mask_kvlen); - ret |= mKernel_qk->get().setArg(index++, mMax_len); + ret |= mKernel_qk->get().setArg(index++, mKeyValueMaxlen); ret |= mKernel_qk->get().setArg(index++, numHead); ret |= mKernel_qk->get().setArg(index++, headDim); MNN_CHECK_CL_SUCCESS(ret, "setArg matmul_qk_div_mask_prefill"); @@ -778,7 +735,7 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c ret |= mKernel_rearrangeV->get().setArg(index++, openCLBuffer(value)); ret |= mKernel_rearrangeV->get().setArg(index++, *mKVCacheCLManager->value()); ret |= mKernel_rearrangeV->get().setArg(index++, past_len); - ret |= mKernel_rearrangeV->get().setArg(index++, mMax_len); + ret |= mKernel_rearrangeV->get().setArg(index++, mKeyValueMaxlen); ret |= mKernel_rearrangeV->get().setArg(index++, seq_len); ret |= mKernel_rearrangeV->get().setArg(index++, kvNumHead); ret |= mKernel_rearrangeV->get().setArg(index++, headDim); @@ -808,7 +765,7 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c ret |= mKernel_qkv->get().setArg(index++, openCLBuffer(outputs[0])); ret |= mKernel_qkv->get().setArg(index++, seq_len); ret |= mKernel_qkv->get().setArg(index++, mask_kvlen); - ret |= mKernel_qkv->get().setArg(index++, mMax_len); + ret |= mKernel_qkv->get().setArg(index++, mKeyValueMaxlen); ret |= mKernel_qkv->get().setArg(index++, numHead); ret |= mKernel_qkv->get().setArg(index++, kvNumHead); ret |= mKernel_qkv->get().setArg(index++, headDim); @@ -820,7 +777,16 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c mGlobalWorkSizeQkv[2] = ROUND_UP(mGlobalWorkSizeQkv[2], std::max((uint32_t)1, mLocalWorkSizeQkv[2])); mOpenCLBackend->recordKernel3d(mKernel_qkv, mGlobalWorkSizeQkv, mLocalWorkSizeQkv); } - }else{ + } else { + mKv_seq_len = mKVCacheCLManager->kvLength() + 1; + mKeyValueMaxlen = ROUND_UP(mKVCacheCLManager->maxLength(), 4); + mDecodeTmpMaxlen = mKeyValueMaxlen; + mTempQK.reset(Tensor::createDevice({mDecodeTmpMaxlen * numHead})); + mTempSoftMax.reset(Tensor::createDevice({mDecodeTmpMaxlen * numHead})); + mOpenCLBackend->onAcquireBuffer(mTempQK.get(), Backend::DYNAMIC_IN_EXECUTION); + mOpenCLBackend->onAcquireBuffer(mTempSoftMax.get(), Backend::DYNAMIC_IN_EXECUTION); + mOpenCLBackend->onReleaseBuffer(mTempQK.get(), Backend::DYNAMIC_IN_EXECUTION); + mOpenCLBackend->onReleaseBuffer(mTempSoftMax.get(), Backend::DYNAMIC_IN_EXECUTION); { // rearrange key std::set buildOption; @@ -840,7 +806,7 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c ret |= mKernel_rearrange->get().setArg(index++, openCLBuffer(key)); ret |= mKernel_rearrange->get().setArg(index++, *mKVCacheCLManager->key()); ret |= mKernel_rearrange->get().setArg(index++, mKv_seq_len); - ret |= mKernel_rearrange->get().setArg(index++, mMax_len); + ret |= mKernel_rearrange->get().setArg(index++, mKeyValueMaxlen); ret |= mKernel_rearrange->get().setArg(index++, seq_len); ret |= mKernel_rearrange->get().setArg(index++, kvNumHead); ret |= mKernel_rearrange->get().setArg(index++, numHead); @@ -853,7 +819,7 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c mGlobalWorkSizeRearrg[2] = ROUND_UP(mGlobalWorkSizeRearrg[2], std::max((uint32_t)1, mLocalWorkSizeRearrg[2])); mRgUpdateInfo.update_kernel_args.push_back({0, 4, sizeof(cl_mem), &(*(mKVCacheCLManager->key()))()}); mRgUpdateInfo.update_kernel_args.push_back({0, 5, sizeof(mKv_seq_len), &mKv_seq_len}); - mRgUpdateInfo.update_kernel_args.push_back({0, 6, sizeof(mMax_len), &mMax_len}); + mRgUpdateInfo.update_kernel_args.push_back({0, 6, sizeof(mKeyValueMaxlen), &mKeyValueMaxlen}); mOpRecordUpdateInfo.emplace_back(&mRgUpdateInfo); mOpenCLBackend->recordKernel3d(mKernel_rearrange, mGlobalWorkSizeRearrg, mLocalWorkSizeRearrg, &mRgUpdateInfo); } @@ -874,10 +840,10 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c ret |= mKernel_qk->get().setArg(index++, mGlobalWorkSizeQk[1]); ret |= mKernel_qk->get().setArg(index++, openCLBuffer(query)); ret |= mKernel_qk->get().setArg(index++, *mKVCacheCLManager->key()); - ret |= mKernel_qk->get().setArg(index++, openCLBuffer(mTempQK.get())); + ret |= mKernel_qk->get().setArg(index++, openCLDeferBuffer(mTempQK.get())); ret |= mKernel_qk->get().setArg(index++, scale); ret |= mKernel_qk->get().setArg(index++, mKv_seq_len); - ret |= mKernel_qk->get().setArg(index++, mMax_len); + ret |= mKernel_qk->get().setArg(index++, mKeyValueMaxlen); ret |= mKernel_qk->get().setArg(index++, numHead); ret |= mKernel_qk->get().setArg(index++, headDim); MNN_CHECK_CL_SUCCESS(ret, "setArg matmul_qk_decode"); @@ -887,9 +853,9 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c mGlobalWorkSizeQk[1] = ROUND_UP(mGlobalWorkSizeQk[1], std::max((uint32_t)1, mLocalWorkSizeQk[1])); mQkUpdateInfo.update_kernel_args.push_back({0, 0, sizeof(mGlobalWorkSizeQk0), &mGlobalWorkSizeQk0}); mQkUpdateInfo.update_kernel_args.push_back({0, 3, sizeof(cl_mem), &(*(mKVCacheCLManager->key()))()}); - mQkUpdateInfo.update_kernel_args.push_back({0, 4, sizeof(cl_mem), &openCLBuffer(mTempQK.get())()}); + mQkUpdateInfo.update_kernel_args.push_back({0, 4, sizeof(cl_mem), &openCLDeferBuffer(mTempQK.get())()}); mQkUpdateInfo.update_kernel_args.push_back({0, 6, sizeof(mKv_seq_len), &mKv_seq_len}); - mQkUpdateInfo.update_kernel_args.push_back({0, 7, sizeof(mMax_len), &mMax_len}); + mQkUpdateInfo.update_kernel_args.push_back({0, 7, sizeof(mKeyValueMaxlen), &mKeyValueMaxlen}); mQkGlobal_size[0] = mGlobalWorkSizeQk[0]; mQkGlobal_size[1] = mGlobalWorkSizeQk[1]; mQkUpdateInfo.update_global_size.push_back({0, mQkGlobal_size}); @@ -916,8 +882,8 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c ret |= mKernel_softmax->get().setArg(index++, mGlobalWorkSizeSoftMax[0]); ret |= mKernel_softmax->get().setArg(index++, mGlobalWorkSizeSoftMax[1]); ret |= mKernel_softmax->get().setArg(index++, mGlobalWorkSizeSoftMax[2]); - ret |= mKernel_softmax->get().setArg(index++, openCLBuffer(mTempQK.get())); - ret |= mKernel_softmax->get().setArg(index++, openCLBuffer(mTempSoftMax.get())); + ret |= mKernel_softmax->get().setArg(index++, openCLDeferBuffer(mTempQK.get())); + ret |= mKernel_softmax->get().setArg(index++, openCLDeferBuffer(mTempSoftMax.get())); ret |= mKernel_softmax->get().setArg(index++, inside); ret |= mKernel_softmax->get().setArg(index++, outside); ret |= mKernel_softmax->get().setArg(index++, mKv_seq_len); @@ -930,8 +896,8 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c mGlobalWorkSizeSoftMax[0] = ROUND_UP(mGlobalWorkSizeSoftMax[0], std::max((uint32_t)1, mLocalWorkSizeSoftMax[0])); mGlobalWorkSizeSoftMax[1] = ROUND_UP(mGlobalWorkSizeSoftMax[1], std::max((uint32_t)1, mLocalWorkSizeSoftMax[1])); mGlobalWorkSizeSoftMax[2] = ROUND_UP(mGlobalWorkSizeSoftMax[2], std::max((uint32_t)1, mLocalWorkSizeSoftMax[2])); - mSoftMaxUpdateInfo.update_kernel_args.push_back({0, 3, sizeof(cl_mem), &openCLBuffer(mTempQK.get())()}); - mSoftMaxUpdateInfo.update_kernel_args.push_back({0, 4, sizeof(cl_mem), &openCLBuffer(mTempSoftMax.get())()}); + mSoftMaxUpdateInfo.update_kernel_args.push_back({0, 3, sizeof(cl_mem), &openCLDeferBuffer(mTempQK.get())()}); + mSoftMaxUpdateInfo.update_kernel_args.push_back({0, 4, sizeof(cl_mem), &openCLDeferBuffer(mTempSoftMax.get())()}); mSoftMaxUpdateInfo.update_kernel_args.push_back({0, 7, sizeof(mKv_seq_len), &mKv_seq_len}); mOpRecordUpdateInfo.emplace_back(&mSoftMaxUpdateInfo); mOpenCLBackend->recordKernel3d(mKernel_softmax, mGlobalWorkSizeSoftMax, mLocalWorkSizeSoftMax, &mSoftMaxUpdateInfo); @@ -955,7 +921,7 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c ret |= mKernel_rearrangeV->get().setArg(index++, openCLBuffer(value)); ret |= mKernel_rearrangeV->get().setArg(index++, *mKVCacheCLManager->value()); ret |= mKernel_rearrangeV->get().setArg(index++, mKv_seq_len); - ret |= mKernel_rearrangeV->get().setArg(index++, mMax_len); + ret |= mKernel_rearrangeV->get().setArg(index++, mKeyValueMaxlen); ret |= mKernel_rearrangeV->get().setArg(index++, seq_len); ret |= mKernel_rearrangeV->get().setArg(index++, kvNumHead); ret |= mKernel_rearrangeV->get().setArg(index++, headDim); @@ -967,7 +933,7 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c mGlobalWorkSizeRearrgV[2] = ROUND_UP(mGlobalWorkSizeRearrgV[2], std::max((uint32_t)1, mLocalWorkSizeRearrgV[2])); mRgVUpdateInfo.update_kernel_args.push_back({0, 4, sizeof(cl_mem), &(*(mKVCacheCLManager->value()))()}); mRgVUpdateInfo.update_kernel_args.push_back({0, 5, sizeof(mKv_seq_len), &mKv_seq_len}); - mRgVUpdateInfo.update_kernel_args.push_back({0, 6, sizeof(mMax_len), &mMax_len}); + mRgVUpdateInfo.update_kernel_args.push_back({0, 6, sizeof(mKeyValueMaxlen), &mKeyValueMaxlen}); mOpRecordUpdateInfo.emplace_back(&mRgVUpdateInfo); mOpenCLBackend->recordKernel3d(mKernel_rearrangeV, mGlobalWorkSizeRearrgV, mLocalWorkSizeRearrgV, &mRgVUpdateInfo); } @@ -997,11 +963,11 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c cl_int ret = CL_SUCCESS; ret |= kernel[knl_idx]->get().setArg(index++, globalWorkSize[knl_idx][0]); ret |= kernel[knl_idx]->get().setArg(index++, globalWorkSize[knl_idx][1]); - ret |= kernel[knl_idx]->get().setArg(index++, openCLBuffer(mTempSoftMax.get())); + ret |= kernel[knl_idx]->get().setArg(index++, openCLDeferBuffer(mTempSoftMax.get())); ret |= kernel[knl_idx]->get().setArg(index++, *mKVCacheCLManager->value()); ret |= kernel[knl_idx]->get().setArg(index++, openCLBuffer(outputs[0])); ret |= kernel[knl_idx]->get().setArg(index++, mKv_seq_len); - ret |= kernel[knl_idx]->get().setArg(index++, mMax_len); + ret |= kernel[knl_idx]->get().setArg(index++, mKeyValueMaxlen); ret |= kernel[knl_idx]->get().setArg(index++, numHead); ret |= kernel[knl_idx]->get().setArg(index++, kvNumHead); ret |= kernel[knl_idx]->get().setArg(index++, headDim); @@ -1025,11 +991,11 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c cl_int ret = CL_SUCCESS; ret |= mKernel_qkv->get().setArg(index++, mGlobalWorkSizeQkv[0]); ret |= mKernel_qkv->get().setArg(index++, mGlobalWorkSizeQkv[1]); - ret |= mKernel_qkv->get().setArg(index++, openCLBuffer(mTempSoftMax.get())); + ret |= mKernel_qkv->get().setArg(index++, openCLDeferBuffer(mTempSoftMax.get())); ret |= mKernel_qkv->get().setArg(index++, *mKVCacheCLManager->value()); ret |= mKernel_qkv->get().setArg(index++, openCLBuffer(outputs[0])); ret |= mKernel_qkv->get().setArg(index++, mKv_seq_len); - ret |= mKernel_qkv->get().setArg(index++, mMax_len); + ret |= mKernel_qkv->get().setArg(index++, mKeyValueMaxlen); ret |= mKernel_qkv->get().setArg(index++, numHead); ret |= mKernel_qkv->get().setArg(index++, kvNumHead); ret |= mKernel_qkv->get().setArg(index++, headDim); @@ -1037,10 +1003,10 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c mGlobalWorkSizeQkv[0] = ROUND_UP(mGlobalWorkSizeQkv[0], std::max((uint32_t)1, mLocalWorkSizeQkv[0])); mGlobalWorkSizeQkv[1] = ROUND_UP(mGlobalWorkSizeQkv[1], std::max((uint32_t)1, mLocalWorkSizeQkv[1])); - mQkvUpdateInfo.update_kernel_args.push_back({0, 2, sizeof(cl_mem), &openCLBuffer(mTempSoftMax.get())()}); + mQkvUpdateInfo.update_kernel_args.push_back({0, 2, sizeof(cl_mem), &openCLDeferBuffer(mTempSoftMax.get())()}); mQkvUpdateInfo.update_kernel_args.push_back({0, 3, sizeof(cl_mem), &(*(mKVCacheCLManager->value()))()}); mQkvUpdateInfo.update_kernel_args.push_back({0, 5, sizeof(mKv_seq_len), &mKv_seq_len}); - mQkvUpdateInfo.update_kernel_args.push_back({0, 6, sizeof(mMax_len), &mMax_len}); + mQkvUpdateInfo.update_kernel_args.push_back({0, 6, sizeof(mKeyValueMaxlen), &mKeyValueMaxlen}); mOpRecordUpdateInfo.emplace_back(&mQkvUpdateInfo); mOpenCLBackend->recordKernel2d(mKernel_qkv, mGlobalWorkSizeQkv, mLocalWorkSizeQkv, &mQkvUpdateInfo); } @@ -1050,19 +1016,118 @@ ErrorCode AttentionBufExecution::onResize(const std::vector &inputs, c return NO_ERROR; } +ErrorCode AttentionBufExecution::DecodeSetArgs(const std::vector &inputs, const std::vector &outputs){ + auto query = inputs[0]; + auto key = inputs[1]; + auto value = inputs[2]; + auto mask = inputs[3]; + auto shape = query->shape(); + + int batch = shape[0]; + int seq_len = shape[1]; + int numHead = shape[2]; + int kvNumHead = key->shape()[2]; + int headDim = shape[3]; + int group_size = numHead / kvNumHead; + float scale = 1.0 / sqrt(headDim); + + mKv_seq_len = mKVCacheCLManager->kvLength() + 1; + mKeyValueMaxlen = ROUND_UP(mKVCacheCLManager->maxLength(), 4); + mKVCacheCLManager->addKvLength(); + if(mKv_seq_len > mDecodeTmpMaxlen){ + mDecodeTmpMaxlen = mKeyValueMaxlen; + mTempQK.reset(Tensor::createDevice({mDecodeTmpMaxlen * numHead})); + mTempSoftMax.reset(Tensor::createDevice({mDecodeTmpMaxlen * numHead})); + mOpenCLBackend->onAcquireBuffer(mTempQK.get(), Backend::DYNAMIC_IN_EXECUTION); + mOpenCLBackend->onAcquireBuffer(mTempSoftMax.get(), Backend::DYNAMIC_IN_EXECUTION); + mOpenCLBackend->onReleaseBuffer(mTempQK.get(), Backend::DYNAMIC_IN_EXECUTION); + mOpenCLBackend->onReleaseBuffer(mTempSoftMax.get(), Backend::DYNAMIC_IN_EXECUTION); + } + mGlobalWorkSizeQk0 = UP_DIV(mKv_seq_len, 4); + mQkGlobal_size[0] = ROUND_UP(mGlobalWorkSizeQk0, std::max((uint32_t)1, mLocalWorkSizeQk[0])); + mGlobalWorkSizeQk[0] = mQkGlobal_size[0]; + +#ifndef ENABLE_OPENCL_TIME_PROFILER + if(mOpenCLBackend->isUseRecordQueue()){ + mRgUpdateInfo.update_kernel_args[0].arg_value = &(*(mKVCacheCLManager->key()))(); + mQkUpdateInfo.update_kernel_args[1].arg_value = &(*(mKVCacheCLManager->key()))(); + mQkUpdateInfo.update_kernel_args[2].arg_value = &openCLDeferBuffer(mTempQK.get())(); + mSoftMaxUpdateInfo.update_kernel_args[0].arg_value = &openCLDeferBuffer(mTempQK.get())(); + mSoftMaxUpdateInfo.update_kernel_args[1].arg_value = &openCLDeferBuffer(mTempSoftMax.get())(); + mRgVUpdateInfo.update_kernel_args[0].arg_value = &(*(mKVCacheCLManager->value()))(); + mQkvUpdateInfo.update_kernel_args[0].arg_value = &openCLDeferBuffer(mTempSoftMax.get())(); + mQkvUpdateInfo.update_kernel_args[1].arg_value = &(*(mKVCacheCLManager->value()))(); + } else { +#endif + { + // rearrange key + uint32_t index = 4; + cl_int ret = CL_SUCCESS; + ret |= mKernel_rearrange->get().setArg(index++, *mKVCacheCLManager->key()); + ret |= mKernel_rearrange->get().setArg(index++, mKv_seq_len); + ret |= mKernel_rearrange->get().setArg(index++, mKeyValueMaxlen); + MNN_CHECK_CL_SUCCESS(ret, "reSetArg rearrange_k"); + } + { + // matmul qk + uint32_t index = 0; + cl_int ret = CL_SUCCESS; + ret |= mKernel_qk->get().setArg(index++, mGlobalWorkSizeQk0); + index++; + index++; + ret |= mKernel_qk->get().setArg(index++, *mKVCacheCLManager->key()); + ret |= mKernel_qk->get().setArg(index++, openCLDeferBuffer(mTempQK.get())); + index++; + ret |= mKernel_qk->get().setArg(index++, mKv_seq_len); + ret |= mKernel_qk->get().setArg(index++, mKeyValueMaxlen); + mGlobalWorkSizeQk[0] = ROUND_UP(mGlobalWorkSizeQk[0], std::max((uint32_t)1, mLocalWorkSizeQk[0])); + mGlobalWorkSizeQk[1] = ROUND_UP(mGlobalWorkSizeQk[1], std::max((uint32_t)1, mLocalWorkSizeQk[1])); + MNN_CHECK_CL_SUCCESS(ret, "reSetArg matmul_qk_decode"); + } + { + // softmax + uint32_t index = 3; + cl_int ret = CL_SUCCESS; + ret |= mKernel_softmax->get().setArg(index++, openCLDeferBuffer(mTempQK.get())); + ret |= mKernel_softmax->get().setArg(index++, openCLDeferBuffer(mTempSoftMax.get())); + index++; + index++; + ret |= mKernel_softmax->get().setArg(index++, mKv_seq_len); + MNN_CHECK_CL_SUCCESS(ret, "reSetArg softmax"); + } + { + uint32_t index = 4; + cl_int ret = CL_SUCCESS; + ret |= mKernel_rearrangeV->get().setArg(index++, *mKVCacheCLManager->value()); + ret |= mKernel_rearrangeV->get().setArg(index++, mKv_seq_len); + ret |= mKernel_rearrangeV->get().setArg(index++, mKeyValueMaxlen); + + MNN_CHECK_CL_SUCCESS(ret, "reSetArg rearrange_v"); + } + // qk * value + { + uint32_t index = 2; + cl_int ret = CL_SUCCESS; + ret |= mKernel_qkv->get().setArg(index++, openCLDeferBuffer(mTempSoftMax.get())); + ret |= mKernel_qkv->get().setArg(index++, *mKVCacheCLManager->value()); + index++; + ret |= mKernel_qkv->get().setArg(index++, mKv_seq_len); + ret |= mKernel_qkv->get().setArg(index++, mKeyValueMaxlen); + MNN_CHECK_CL_SUCCESS(ret, "reSetArg matmul_qkv_decode"); + } +#ifndef ENABLE_OPENCL_TIME_PROFILER + } +#endif + return NO_ERROR; +} + ErrorCode AttentionBufExecution::onExecute(const std::vector &inputs, const std::vector &outputs) { #ifdef LOG_VERBOSE MNN_PRINT("start AttentionBufExecution onExecute !\n"); #endif if(mIsDecode){ - if(mKVCacheCLManager->reallocKVCache()){ - reallocKVCache(); - } - mKv_seq_len = mKVCacheCLManager->kvLength() + 1; - mGlobalWorkSizeQk0 = UP_DIV(mKv_seq_len, 4); - mQkGlobal_size[0] = ROUND_UP(mGlobalWorkSizeQk0, std::max((uint32_t)1, mLocalWorkSizeQk[0])); - mGlobalWorkSizeQk[0] = mQkGlobal_size[0]; - mKVCacheCLManager->addKvLength(); + mKVCacheCLManager->reallocKVCache(); + DecodeSetArgs(inputs, outputs); } #ifdef ENABLE_OPENCL_TIME_PROFILER if(mLongPrefill) { @@ -1119,17 +1184,6 @@ ErrorCode AttentionBufExecution::onExecute(const std::vector &inputs, return NO_ERROR; } - // decode - if(mIsDecode){ - cl_int ret = CL_SUCCESS; - ret |= mKernel_rearrange->get().setArg(5, mKv_seq_len); - ret |= mKernel_qk->get().setArg(0, mGlobalWorkSizeQk0); - ret |= mKernel_qk->get().setArg(6, mKv_seq_len); - ret |= mKernel_softmax->get().setArg(7, mKv_seq_len); - ret |= mKernel_rearrangeV->get().setArg(5, mKv_seq_len); - ret |= mKernel_qkv->get().setArg(5, mKv_seq_len); - MNN_CHECK_CL_SUCCESS(ret, "reset arg for AttentionBufExecution"); - } if(mLongPrefill) { run3DKernelDefault(mKernel_rearrange, mGlobalWorkSizeRearrg, mLocalWorkSizeRearrg, mOpenCLBackend->getOpenCLRuntime()); run3DKernelDefault(mKernel_mask, mGlobalWorkSizeMask, mLocalWorkSizeMask, mOpenCLBackend->getOpenCLRuntime()); diff --git a/source/backend/opencl/execution/buffer/AttentionBufExecution.hpp b/source/backend/opencl/execution/buffer/AttentionBufExecution.hpp index 5089f968a..0f617981c 100644 --- a/source/backend/opencl/execution/buffer/AttentionBufExecution.hpp +++ b/source/backend/opencl/execution/buffer/AttentionBufExecution.hpp @@ -62,6 +62,7 @@ class AttentionBufExecution : public CommonExecution { AttentionBufExecution(const MNN::Op *op, Backend *backend, bool kv_cache); AttentionBufExecution(std::shared_ptr manager, const MNN::Op *op, Backend *backend); ErrorCode longPrefillResize(const std::vector &inputs, const std::vector &outputs); + ErrorCode DecodeSetArgs(const std::vector &inputs, const std::vector &outputs); virtual ~AttentionBufExecution() = default; virtual ErrorCode onResize(const std::vector &inputs, const std::vector &outputs) override; @@ -71,11 +72,11 @@ class AttentionBufExecution : public CommonExecution { private: int getLocalSize(int size, int maxGroupSize); - void reallocKVCache(); bool mIsDecode = false; bool mIsFirstPrefill = true; int mKv_seq_len = 0; - int mMax_len = 0; + int mKeyValueMaxlen = 0; + int mDecodeTmpMaxlen = 0; std::shared_ptr mKernel_qk; std::shared_ptr mKernel_softmax; std::shared_ptr mKernel_qkv; diff --git a/source/backend/opencl/execution/buffer/ConvBufExecution.cpp b/source/backend/opencl/execution/buffer/ConvBufExecution.cpp index 00f48dbce..87cbdc5cf 100644 --- a/source/backend/opencl/execution/buffer/ConvBufExecution.cpp +++ b/source/backend/opencl/execution/buffer/ConvBufExecution.cpp @@ -252,6 +252,7 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const #ifdef LOG_VERBOSE MNN_PRINT("Start ConvExecution onResize !\n"); #endif + mKernel.resize(1); auto input = inputs[0]; auto output = outputs[0]; if (inputs.size() > 1) { @@ -290,12 +291,10 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const int N = outputShape.at(3); int K = inputShape.at(3); + // total computation not enough if(M < 128 || 1.0 * M / 512 * N / 512 * K / 256 < 1.0) { mResource->mConvGemmOptLevel = 0; } - if(1.0 * M * N / K / K > 100.0 || 1.0 * M * K / N / N > 100.0) { - mResource->mConvGemmOptLevel = 0; - } } if (mResource->mConvGemmOptLevel == 1) { @@ -413,21 +412,21 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const std::set buildOption = mResource->mBuildOptions; buildOption.emplace("-DCONV_LOCAL_SIZE=" + std::to_string(local_size)); - mKernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d_buf", "conv_2d_1x1_local", buildOption); + mKernel[0] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d_buf", "conv_2d_1x1_local", buildOption); uint32_t idx = 0; cl_int ret = CL_SUCCESS; - ret |= mKernel->get().setArg(idx++, UP_DIV(width, 1)); - ret |= mKernel->get().setArg(idx++, openCLBuffer(input)); - ret |= mKernel->get().setArg(idx++, openCLBuffer(mResource->mFilter.get())); - ret |= mKernel->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); - ret |= mKernel->get().setArg(idx++, openCLBuffer(output)); - ret |= mKernel->get().setArg(idx++, static_cast(inputChannelBlocks)); - ret |= mKernel->get().setArg(idx++, batch); - ret |= mKernel->get().setArg(idx++, height); - ret |= mKernel->get().setArg(idx++, width); - ret |= mKernel->get().setArg(idx++, UP_DIV(outChannel, 4)); - ret |= mKernel->get().setArg(idx++, ROUND_UP(outChannel, mResource->mAlignN)); + ret |= mKernel[0]->get().setArg(idx++, UP_DIV(width, 1)); + ret |= mKernel[0]->get().setArg(idx++, openCLBuffer(input)); + ret |= mKernel[0]->get().setArg(idx++, openCLBuffer(mResource->mFilter.get())); + ret |= mKernel[0]->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); + ret |= mKernel[0]->get().setArg(idx++, openCLBuffer(output)); + ret |= mKernel[0]->get().setArg(idx++, static_cast(inputChannelBlocks)); + ret |= mKernel[0]->get().setArg(idx++, batch); + ret |= mKernel[0]->get().setArg(idx++, height); + ret |= mKernel[0]->get().setArg(idx++, width); + ret |= mKernel[0]->get().setArg(idx++, UP_DIV(outChannel, 4)); + ret |= mKernel[0]->get().setArg(idx++, ROUND_UP(outChannel, mResource->mAlignN)); MNN_CHECK_CL_SUCCESS(ret, "setArg Conv1x1Buf"); } else { mResource->mConv1x1Local = false; @@ -506,23 +505,23 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const if((outputShape.at(2) % itemW[min_index]) != 0){ buildOption.emplace("-DBLOCK_LEAVE"); } - mKernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d_buf", kernelName[min_index], buildOption); + mKernel[0] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d_buf", kernelName[min_index], buildOption); uint32_t idx = 0; cl_int ret = CL_SUCCESS; - ret |= mKernel->get().setArg(idx++, mGlobalWorkSize[0]); - ret |= mKernel->get().setArg(idx++, mGlobalWorkSize[1]); - ret |= mKernel->get().setArg(idx++, UP_DIV(width, itemW[min_index])); - ret |= mKernel->get().setArg(idx++, openCLBuffer(input)); - ret |= mKernel->get().setArg(idx++, openCLBuffer(mResource->mFilter.get())); - ret |= mKernel->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); - ret |= mKernel->get().setArg(idx++, openCLBuffer(output)); - ret |= mKernel->get().setArg(idx++, static_cast(inputChannelBlocks)); - ret |= mKernel->get().setArg(idx++, height); - ret |= mKernel->get().setArg(idx++, width); - ret |= mKernel->get().setArg(idx++, batch); - ret |= mKernel->get().setArg(idx++, UP_DIV(outChannel, 4)); - ret |= mKernel->get().setArg(idx++, ROUND_UP(outChannel, mResource->mAlignN)); + ret |= mKernel[0]->get().setArg(idx++, mGlobalWorkSize[0]); + ret |= mKernel[0]->get().setArg(idx++, mGlobalWorkSize[1]); + ret |= mKernel[0]->get().setArg(idx++, UP_DIV(width, itemW[min_index])); + ret |= mKernel[0]->get().setArg(idx++, openCLBuffer(input)); + ret |= mKernel[0]->get().setArg(idx++, openCLBuffer(mResource->mFilter.get())); + ret |= mKernel[0]->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); + ret |= mKernel[0]->get().setArg(idx++, openCLBuffer(output)); + ret |= mKernel[0]->get().setArg(idx++, static_cast(inputChannelBlocks)); + ret |= mKernel[0]->get().setArg(idx++, height); + ret |= mKernel[0]->get().setArg(idx++, width); + ret |= mKernel[0]->get().setArg(idx++, batch); + ret |= mKernel[0]->get().setArg(idx++, UP_DIV(outChannel, 4)); + ret |= mKernel[0]->get().setArg(idx++, ROUND_UP(outChannel, mResource->mAlignN)); MNN_CHECK_CL_SUCCESS(ret, "setArg Conv1x1Buf"); } } else { @@ -535,23 +534,37 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const // {"conv_2d_c4h1w2", "conv_2d_c4h1w1", "conv_2d_c8h1w1", "conv_2d_c4h1w4", "conv_2d_c8h2w1", "conv_2d_c4h4w1"}; const int total_kernel = 7; - std::string kernelName[total_kernel] = {"conv_2d_c4h1w1", "conv_2d_c4h1w2", "conv_2d_c4h4w1", "conv_2d_c8h2w1", "conv_2d_c8h4w1", "conv_2d_c4h1w4", "conv_2d_c8h1w4"}; - int itemC[total_kernel] = {4, 4, 4, 8, 8, 4, 8}; - int itemH[total_kernel] = {1, 1, 4, 2, 4, 1, 1}; - int itemW[total_kernel] = {1, 2, 1, 1, 1, 4, 4}; - + std::string kernelName[total_kernel] = {"conv_2d_c4h1w1", "conv_2d_c4h1w2", "conv_2d_c4h4w1", "conv_2d_c4h1w4", "conv_2d_c8h2w1", "conv_2d_c8h4w1", "conv_2d_c8h1w4"}; + int itemC[total_kernel] = {4, 4, 4, 4, 8, 8, 8}; + int itemH[total_kernel] = {1, 1, 4, 1, 2, 4, 1}; + int itemW[total_kernel] = {1, 2, 1, 4, 1, 1, 4}; int actual_kernel = total_kernel; + int outChannelBlocks = UP_DIV(outChannel, 4); + int conv_block_num = 1; + auto magic_ratio = 1.0 * outputShape.at(0) * outputShape.at(1) * outputShape.at(2) / 1024.0 * \ + inputChannels * kernelShape[0] * kernelShape[1] / 1024.0 * \ + outChannel / 1024.0; + if(magic_ratio >= 16.0 && outChannelBlocks >= 64) { + conv_block_num = 8; + } else if(magic_ratio >= 8.0 && outChannelBlocks >= 32) { + conv_block_num = 4; + } else if(magic_ratio >= 4.0 && outChannelBlocks >= 16) { + conv_block_num = 2; + } else { + conv_block_num = 1; + } - - std::shared_ptr kernel[total_kernel]; - std::vector globalWorkSize[total_kernel]; - std::vector localWorkSize[total_kernel]; + mKernel.resize(conv_block_num); + + std::shared_ptr kernel[actual_kernel]; + std::vector globalWorkSize[actual_kernel]; + std::vector localWorkSize[actual_kernel]; std::pair min_cost(INT_MAX, 0);//(min_time, min_index) for(int knl_idx = 0; knl_idx < actual_kernel; knl_idx++) { std::set buildOption = mResource->mBuildOptions; if(outputShape.at(3) % itemC[knl_idx] != 0){ - buildOption.emplace("-DCHANNEL_LEAVE"); + buildOption.emplace("-DCHANNEL_BOUNDARY_PROTECT"); } if((outputShape.at(2) % itemW[knl_idx]) != 0 || (outputShape.at(1) % itemH[knl_idx]) != 0){ buildOption.emplace("-DBLOCK_LEAVE"); @@ -559,7 +572,9 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const kernel[knl_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d_buf", kernelName[knl_idx], buildOption); uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel[knl_idx])); - globalWorkSize[knl_idx] = {static_cast(UP_DIV(outputShape.at(3), itemC[knl_idx]) * UP_DIV(outputShape.at(2), itemW[knl_idx])), static_cast(outputShape.at(0) * UP_DIV(outputShape.at(1), itemH[knl_idx]))}; + int each_oc = (UP_DIV(outputShape.at(3), itemC[knl_idx]) + conv_block_num - 1) / conv_block_num; + + globalWorkSize[knl_idx] = {static_cast(each_oc * UP_DIV(outputShape.at(2), itemW[knl_idx])), static_cast(outputShape.at(0) * UP_DIV(outputShape.at(1), itemH[knl_idx]))}; uint32_t idx = 0; cl_int ret = CL_SUCCESS; ret |= kernel[knl_idx]->get().setArg(idx++, globalWorkSize[knl_idx][0]); @@ -578,8 +593,10 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const ret |= kernel[knl_idx]->get().setArg(idx++, sizeof(paddingShape), paddingShape); ret |= kernel[knl_idx]->get().setArg(idx++, sizeof(dilationShape), dilationShape); ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(width, itemW[knl_idx])); - ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(outChannel, 4)); + ret |= kernel[knl_idx]->get().setArg(idx++, outChannelBlocks); ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(height, itemH[knl_idx])); + int outChannelBase = 0; + ret |= kernel[knl_idx]->get().setArg(idx++, outChannelBase); MNN_CHECK_CL_SUCCESS(ret, "setArg ConvBuf Kernel Select"); std::pair, int> retTune; @@ -596,43 +613,50 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const std::set buildOption = mResource->mBuildOptions; if(outputShape.at(3) % itemC[min_index] != 0){ - buildOption.emplace("-DCHANNEL_LEAVE"); + buildOption.emplace("-DCHANNEL_BOUNDARY_PROTECT"); } if((outputShape.at(2) % itemW[min_index]) != 0 || (outputShape.at(1) % itemH[min_index]) != 0){ buildOption.emplace("-DBLOCK_LEAVE"); } - mKernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d_buf", kernelName[min_index], buildOption); - - uint32_t idx = 0; - cl_int ret = CL_SUCCESS; - - ret |= mKernel->get().setArg(idx++, mGlobalWorkSize[0]); - ret |= mKernel->get().setArg(idx++, mGlobalWorkSize[1]); - ret |= mKernel->get().setArg(idx++, openCLBuffer(input)); - ret |= mKernel->get().setArg(idx++, openCLBuffer(mResource->mFilter.get())); - ret |= mKernel->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); - ret |= mKernel->get().setArg(idx++, openCLBuffer(output)); - ret |= mKernel->get().setArg(idx++, sizeof(inputImageShape), inputImageShape); - ret |= mKernel->get().setArg(idx++, inputChannels); - ret |= mKernel->get().setArg(idx++, inputChannelBlocks); - ret |= mKernel->get().setArg(idx++, batch); - ret |= mKernel->get().setArg(idx++, sizeof(outputImageShape), outputImageShape); - ret |= mKernel->get().setArg(idx++, sizeof(kernelShape), kernelShape); - ret |= mKernel->get().setArg(idx++, sizeof(strideShape), strideShape); - ret |= mKernel->get().setArg(idx++, sizeof(paddingShape), paddingShape); - ret |= mKernel->get().setArg(idx++, sizeof(dilationShape), dilationShape); - ret |= mKernel->get().setArg(idx++, UP_DIV(width, itemW[min_index])); - ret |= mKernel->get().setArg(idx++, UP_DIV(outChannel, 4)); - ret |= mKernel->get().setArg(idx++, UP_DIV(height, itemH[min_index])); - MNN_CHECK_CL_SUCCESS(ret, "setArg ConvBuf"); + + for(int kernel_idx = 0; kernel_idx < conv_block_num; kernel_idx++) { + mKernel[kernel_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d_buf", kernelName[min_index], buildOption); + + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + + ret |= mKernel[kernel_idx]->get().setArg(idx++, mGlobalWorkSize[0]); + ret |= mKernel[kernel_idx]->get().setArg(idx++, mGlobalWorkSize[1]); + ret |= mKernel[kernel_idx]->get().setArg(idx++, openCLBuffer(input)); + ret |= mKernel[kernel_idx]->get().setArg(idx++, openCLBuffer(mResource->mFilter.get())); + ret |= mKernel[kernel_idx]->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); + ret |= mKernel[kernel_idx]->get().setArg(idx++, openCLBuffer(output)); + ret |= mKernel[kernel_idx]->get().setArg(idx++, sizeof(inputImageShape), inputImageShape); + ret |= mKernel[kernel_idx]->get().setArg(idx++, inputChannels); + ret |= mKernel[kernel_idx]->get().setArg(idx++, inputChannelBlocks); + ret |= mKernel[kernel_idx]->get().setArg(idx++, batch); + ret |= mKernel[kernel_idx]->get().setArg(idx++, sizeof(outputImageShape), outputImageShape); + ret |= mKernel[kernel_idx]->get().setArg(idx++, sizeof(kernelShape), kernelShape); + ret |= mKernel[kernel_idx]->get().setArg(idx++, sizeof(strideShape), strideShape); + ret |= mKernel[kernel_idx]->get().setArg(idx++, sizeof(paddingShape), paddingShape); + ret |= mKernel[kernel_idx]->get().setArg(idx++, sizeof(dilationShape), dilationShape); + ret |= mKernel[kernel_idx]->get().setArg(idx++, UP_DIV(width, itemW[min_index])); + ret |= mKernel[kernel_idx]->get().setArg(idx++, outChannelBlocks); + ret |= mKernel[kernel_idx]->get().setArg(idx++, UP_DIV(height, itemH[min_index])); + int outChannelBase = mGlobalWorkSize[0] / UP_DIV(width, itemW[min_index]) * kernel_idx; + ret |= mKernel[kernel_idx]->get().setArg(idx++, outChannelBase); + MNN_CHECK_CL_SUCCESS(ret, "setArg ConvBuf"); + } } if (inputs.size() > 1) { backend()->onReleaseBuffer(mResource->mFilter.get(), Backend::DYNAMIC); } if (mResource->mConv1x1Opt && mResource->mConv1x1Local){ - mOpenCLBackend->recordKernel3d(mKernel, mGlobalWorkSize, mLocalWorkSize); + mOpenCLBackend->recordKernel3d(mKernel[0], mGlobalWorkSize, mLocalWorkSize); }else{ - mOpenCLBackend->recordKernel2d(mKernel, mGlobalWorkSize, mLocalWorkSize); + for(int i = 0; i < mKernel.size(); i++) { + mOpenCLBackend->recordKernel2d(mKernel[i], mGlobalWorkSize, mLocalWorkSize); + } mGlobalWorkSize[0] = ROUND_UP(mGlobalWorkSize[0], std::max((uint32_t)1, mLocalWorkSize[0])); mGlobalWorkSize[1] = ROUND_UP(mGlobalWorkSize[1], std::max((uint32_t)1, mLocalWorkSize[1])); } @@ -671,9 +695,9 @@ ErrorCode ConvBufExecution::onExecute(const std::vector &inputs, const } else { cl::Event event; if (mResource->mConv1x1Opt && mResource->mConv1x1Local){ - run3DKernelDefault(mKernel, mGlobalWorkSize, mLocalWorkSize, mOpenCLBackend->getOpenCLRuntime(), &event); + run3DKernelDefault(mKernel[0], mGlobalWorkSize, mLocalWorkSize, mOpenCLBackend->getOpenCLRuntime(), &event); } else{ - runKernel2D(mKernel, mGlobalWorkSize, mLocalWorkSize, mOpenCLBackend->getOpenCLRuntime(), &event); + runKernel2D(mKernel[0], mGlobalWorkSize, mLocalWorkSize, mOpenCLBackend->getOpenCLRuntime(), &event); } std::string name = "ConvBuf2D"; std::string b = std::to_string(inputs[0]->batch()); @@ -698,6 +722,11 @@ ErrorCode ConvBufExecution::onExecute(const std::vector &inputs, const } name += "-total:" + total + "*10^6"; mOpenCLBackend->getOpenCLRuntime()->pushEvent({name.c_str(), event}); + for(int i = 1; i < mKernel.size(); i++) { + cl::Event event; + runKernel2D(mKernel[i], mGlobalWorkSize, mLocalWorkSize, mOpenCLBackend->getOpenCLRuntime(), &event); + mOpenCLBackend->getOpenCLRuntime()->pushEvent({name.c_str(), event}); + } } if (mPostKernel) { cl::Event event2; @@ -719,9 +748,11 @@ ErrorCode ConvBufExecution::onExecute(const std::vector &inputs, const mStrassenComputor->onExecute(); } else { if (mResource->mConv1x1Opt && mResource->mConv1x1Local){ - run3DKernelDefault(mKernel, mGlobalWorkSize, mLocalWorkSize, mOpenCLBackend->getOpenCLRuntime()); + run3DKernelDefault(mKernel[0], mGlobalWorkSize, mLocalWorkSize, mOpenCLBackend->getOpenCLRuntime()); } else{ - runKernel2D(mKernel, mGlobalWorkSize, mLocalWorkSize, mOpenCLBackend->getOpenCLRuntime()); + for(int i = 0; i < mKernel.size(); i++) { + runKernel2D(mKernel[i], mGlobalWorkSize, mLocalWorkSize, mOpenCLBackend->getOpenCLRuntime()); + } } } if (mPostKernel) { diff --git a/source/backend/opencl/execution/buffer/ConvBufExecution.hpp b/source/backend/opencl/execution/buffer/ConvBufExecution.hpp index b8edea9ef..60e03a36c 100644 --- a/source/backend/opencl/execution/buffer/ConvBufExecution.hpp +++ b/source/backend/opencl/execution/buffer/ConvBufExecution.hpp @@ -76,7 +76,7 @@ class ConvBufExecution : public ConvBufCommonExecution, public CommonExecution { std::vector mPaddings{0, 0}; std::vector mGlobalWorkSize{1, 1, 1}; std::vector mLocalWorkSize{1, 1, 1, 1}; - std::shared_ptr mKernel; + std::vector> mKernel; std::shared_ptr mConvGemmInpTensor; std::shared_ptr mConvGemmOutTensor; std::shared_ptr mPreKernel = nullptr; diff --git a/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.cpp b/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.cpp index 21db9895e..ce9df36b9 100644 --- a/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.cpp +++ b/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.cpp @@ -79,7 +79,7 @@ void ConvBufLowMemoryExecution::getInfoFromOpLowMemory(std::shared_ptrweight.get(); } -bool ConvBufLowMemoryExecution::convertToQuantWeight1x1Buffer(cl::Buffer input, int pack) { +bool ConvBufLowMemoryExecution::convertToQuantWeight1x1Buffer(cl::Buffer input, int packCin, int packCout) { #ifdef LOG_VERBOSE MNN_PRINT("start convertToQuantWeight1x1Buffer !\n"); #endif @@ -95,13 +95,10 @@ bool ConvBufLowMemoryExecution::convertToQuantWeight1x1Buffer(cl::Buffer input, // int4 case buildOptions.emplace("-DUSE_LOW_BIT_WEIGHT_INT4"); } else {/* More types to be supported. */} - if(mResource->mInputChannel % pack != 0){ - buildOptions.emplace("-DCHANNEL_LEAVE"); - } mBufferToConv1x1Kernel = runtime->buildKernelWithCache("buffer_convert_quant", kernelName, buildOptions); auto kernel = mBufferToConv1x1Kernel->get(); - uint32_t gws[2] = {static_cast(UP_DIV(mResource->mInputChannel, pack)), static_cast(mResource->mOutputChannel)}; + uint32_t gws[2] = {static_cast(UP_DIV(mResource->mInputChannel, packCin)), static_cast(UP_DIV(mResource->mOutputChannel, packCout))}; uint32_t idx = 0; cl_int ret = CL_SUCCESS; @@ -147,11 +144,14 @@ void ConvBufLowMemoryExecution::set1x1WeightLowMemory(int packCout, int packCin, std::shared_ptr filterBuffer(Tensor::createDevice({ROUND_UP(mResource->mOutputChannel, packCout), ROUND_UP(mResource->mInputChannel, packCin), 1, 1})); size_t buffer_size = filterBuffer->usize() / sizeof(float); size_t cpy_size = mResource->mOutputChannel * mResource->mInputChannel; + int actual_packCin = packCin; // shared part for all cases if (mResource->mNumQuantBit == 4){ // int4 case buffer_size /= 2; cpy_size = UP_DIV(cpy_size, 2); + } else if(mResource->mNumQuantBit == 8){ + actual_packCin /= 2; } else {/* More types to be supported. */} float *dequantAlpha = quanCommon->alpha.get(); cl::Buffer filterBufferCL(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size); @@ -163,25 +163,22 @@ void ConvBufLowMemoryExecution::set1x1WeightLowMemory(int packCout, int packCin, MNN_ASSERT(false); } mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(filterBufferCL, mapPtr); - + // Use Image load weights - if(UP_DIV(mResource->mInputChannel, packCin) <= 16384 && ROUND_UP(mResource->mOutputChannel, packCout) <= 16384){ + if(UP_DIV(mResource->mInputChannel, actual_packCin) <= 16384 && ROUND_UP(mResource->mOutputChannel, packCout) <= 16384){ mResource->mUseImage = true; } - if(mResource->mUseImage) { - if(mResource->mNumQuantBit == 4){ - packCin *= 2; - } - size_t w = ROUND_UP(mResource->mOutputChannel, packCout); - size_t h = UP_DIV(mResource->mInputChannel, packCin); + if(mResource->mUseImage){ + size_t w = UP_DIV(mResource->mInputChannel, actual_packCin); + size_t h = UP_DIV(mResource->mOutputChannel, packCout); mResource->mKernelImage.reset(new cl::Image2D(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE, cl::ImageFormat(CL_RGBA, CL_SIGNED_INT32), w, h, 0, nullptr, &res)); if (nullptr == mResource->mKernelImage.get() || res != CL_SUCCESS) { MNN_ERROR("Alloc Image %d x %d error, code:%d \n", (int)w, (int)h, (int)res); } - } else{ + }else{ mResource->mKernelBuffer.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size)); } - convertToQuantWeight1x1Buffer(filterBufferCL, packCin); + convertToQuantWeight1x1Buffer(filterBufferCL, packCin, packCout); } // set mFilter for the general kernels void ConvBufLowMemoryExecution::setGeneralWeightLowMemory(void* filterDataPtr, std::shared_ptr & quanCommon) { @@ -359,9 +356,9 @@ void ConvBufLowMemoryExecution::useFPWeightGemmLowMemory(Tensor * input, Tensor auto runtime = mOpenCLBackend->getOpenCLRuntime(); std::vector inputShape = tensorShapeFormat(input); std::vector outputShape = tensorShapeFormat(output); - int channelPack = 16; - if(mResource->mUseImage && mResource->mNumQuantBit == 4){ - channelPack = 32; + int channelPack = 2; + if(mResource->mNumQuantBit == 4){ + channelPack = 4; } int area = inputShape.at(1) * inputShape.at(2); int M = outputShape.at(0) * area; @@ -407,11 +404,12 @@ void ConvBufLowMemoryExecution::useFPWeightGemmLowMemory(Tensor * input, Tensor auto &unit = mUnits[0]; int outputChannelAlign = ROUND_UP(mResource->mOutputChannel, alignN); int outputChannel4Align = ROUND_UP(mResource->mOutputChannel, 4); + int inputChannel4Align = ROUND_UP(mResource->mInputChannel, 4); std::set buildOption = mResource->mBuildOptions; if(mResource->mUseImage){ buildOption.emplace("-DUSE_IMAGE"); } - mGlobalWorkSize = {static_cast(UP_DIV(mResource->mInputChannel, channelPack)), static_cast(UP_DIV(mResource->mOutputChannel, 4))}; + mGlobalWorkSize = {static_cast(UP_DIV(mResource->mInputChannel, channelPack)), static_cast(UP_DIV(mResource->mOutputChannel, 8))}; unit.kernel = runtime->buildKernel("gemm_conv1x1_buf", "inverse_quant_weight", buildOption); uint32_t maxWorkGroupSize = static_cast(runtime->getMaxWorkGroupSize(unit.kernel)); uint32_t idx = 0; @@ -425,6 +423,7 @@ void ConvBufLowMemoryExecution::useFPWeightGemmLowMemory(Tensor * input, Tensor } ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mConvGemmWeightTensor.get())); + ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannel4Align)); ret |= unit.kernel->get().setArg(idx++, static_cast(outputChannelAlign)); ret |= unit.kernel->get().setArg(idx++, static_cast(outputChannel4Align)); ret |= unit.kernel->get().setArg(idx++, static_cast(blockDim)); @@ -528,71 +527,69 @@ void ConvBufLowMemoryExecution::tuneGemvLowMemory(Tensor * input, Tensor * outpu const int outputChannelBlocks = UP_DIV(outChannel, 4); const int blockNum = mResource->mBlockSize; const int blockDim = mResource->mInputChannel / mResource->mBlockSize; - - int global_y = batch * height * width; - const int total_kernel = 3; - std::string kernelName[total_kernel] = {"gemv_conv_c1_buf", "gemv_conv_c2_buf", "gemv_conv_c4_buf"}; - int itemC[total_kernel] = {1, 2, 4}; - int actual_kernel = total_kernel; - std::shared_ptr kernel[total_kernel]; - std::vector globalWorkSize[total_kernel]; - std::vector localWorkSize[total_kernel]; - std::pair min_cost(INT_MAX, 0);//(min_time, min_index) + bool useLocalMem = inputChannels >= 32; + std::string info = std::to_string(inputChannels) + "_" + std::to_string(outChannel); + std::string kernelName = "gemv_conv_c8"; std::set buildOption = mResource->mBuildOptions; - - if(blockDim % 16 != 0){ - buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); - } else if (mResource->mUseImage && mResource->mNumQuantBit == 4 && blockDim % 32 != 0) { - // Image weight-int4 use load32 - buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + int inputChannelLeaves = 0; + if(mResource->mNumQuantBit == 4){ + inputChannelLeaves = useLocalMem ? (inputChannels % 4) : (blockDim % 4); + kernelName += "_int4_buf"; + } else { + inputChannelLeaves = useLocalMem ? (inputChannels % 2) : (blockDim % 2); + kernelName += "_int8_buf"; } - std::string info = std::to_string(inputChannels) + "_" + std::to_string(outChannel); + buildOption.emplace("-DINPUT_CHANNEL_LEAVES_NUM=" + std::to_string(inputChannelLeaves)); if(mResource->mUseImage){ buildOption.emplace("-DUSE_IMAGE"); } - for (int knl_idx = 0; knl_idx < actual_kernel; knl_idx++) { - auto option = buildOption; - option.emplace("-DTILE_N=" + std::to_string(itemC[knl_idx])); - kernel[knl_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemv_conv1x1_buf", kernelName[knl_idx], option); - uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel[knl_idx])); - globalWorkSize[knl_idx] = {static_cast(UP_DIV(outChannel, itemC[knl_idx])), static_cast(global_y)}; - uint32_t idx = 0; - cl_int ret = CL_SUCCESS; - ret |= kernel[knl_idx]->get().setArg(idx++, globalWorkSize[knl_idx][0]); - ret |= kernel[knl_idx]->get().setArg(idx++, globalWorkSize[knl_idx][1]); - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(input)); - if(mResource->mUseImage){ - ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->mKernelImage.get()); - }else{ - ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->mKernelBuffer.get()); - } - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(output)); - ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(outputChannelBlocks)); - ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(inputChannelBlocks)); - ret |= kernel[knl_idx]->get().setArg(idx++, inputChannels); - ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(global_y)); - ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(blockNum)); - ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(blockDim)); - MNN_CHECK_CL_SUCCESS(ret, "setArg gemv_conv1x1_buf Kernel Select"); - std::pair, int> retTune; - retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); - if(min_cost.first > retTune.second) { - min_cost.first = retTune.second; - min_cost.second = knl_idx; - mLocalWorkSize = {retTune.first[0], retTune.first[1]}; + + int local_size = 1; + if(useLocalMem){ + int min_time = INT_MAX; + for (int ksize = 8; ksize <= 256; ksize*=2) { + auto option = buildOption; + option.emplace("-DWGS=" + std::to_string(ksize)); + auto kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemv_conv1x1_buf", kernelName, option); + uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel)); + std::vector gws = {static_cast(ksize), static_cast(UP_DIV(outChannel, 8))}; + std::vector lws = {static_cast(ksize), 1}; + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= kernel->get().setArg(idx++, static_cast(gws[0])); + ret |= kernel->get().setArg(idx++, static_cast(gws[1])); + ret |= kernel->get().setArg(idx++, openCLBuffer(input)); + if(mResource->mUseImage){ + ret |= kernel->get().setArg(idx++, *mResource->mKernelImage.get()); + }else{ + ret |= kernel->get().setArg(idx++, *mResource->mKernelBuffer.get()); + } + ret |= kernel->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); + ret |= kernel->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); + ret |= kernel->get().setArg(idx++, openCLBuffer(output)); + ret |= kernel->get().setArg(idx++, static_cast(outputChannelBlocks)); + ret |= kernel->get().setArg(idx++, static_cast(inputChannelBlocks)); + ret |= kernel->get().setArg(idx++, inputChannels); + ret |= kernel->get().setArg(idx++, static_cast(blockNum)); + ret |= kernel->get().setArg(idx++, static_cast(blockDim)); + MNN_CHECK_CL_SUCCESS(ret, "setArg gemv_conv1x1_buf Kernel Select"); + std::pair, int> retTune; + int cost_time = get2DUseLocalMemTime(gws, lws, mOpenCLBackend->getOpenCLRuntime(), kernelName + info, kernel); + if(min_time > cost_time) { + local_size = ksize; + min_time = cost_time; + } } } - int min_index = min_cost.second; - mGlobalWorkSize = {globalWorkSize[min_index][0], globalWorkSize[min_index][1]}; - buildOption.emplace("-DTILE_N=" + std::to_string(itemC[min_index])); - unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemv_conv1x1_buf", kernelName[min_index], buildOption); + buildOption.emplace("-DWGS=" + std::to_string(local_size)); + mGlobalWorkSize = {static_cast(local_size), static_cast(UP_DIV(outChannel, 8))}; + unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemv_conv1x1_buf", kernelName, buildOption); + uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(unit.kernel)); uint32_t idx = 0; cl_int ret = CL_SUCCESS; - ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]); - ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); + ret |= unit.kernel->get().setArg(idx++, static_cast(mGlobalWorkSize[0])); + ret |= unit.kernel->get().setArg(idx++, static_cast(mGlobalWorkSize[1])); ret |= unit.kernel->get().setArg(idx++, openCLBuffer(input)); if(mResource->mUseImage){ ret |= unit.kernel->get().setArg(idx++, *mResource->mKernelImage.get()); @@ -605,179 +602,81 @@ void ConvBufLowMemoryExecution::tuneGemvLowMemory(Tensor * input, Tensor * outpu ret |= unit.kernel->get().setArg(idx++, static_cast(outputChannelBlocks)); ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannelBlocks)); ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannels)); - ret |= unit.kernel->get().setArg(idx++, static_cast(global_y)); ret |= unit.kernel->get().setArg(idx++, static_cast(blockNum)); ret |= unit.kernel->get().setArg(idx++, static_cast(blockDim)); - MNN_CHECK_CL_SUCCESS(ret, "setArg gemv_conv1x1_buf"); + MNN_CHECK_CL_SUCCESS(ret, "setArg gemv_conv_c4_0_buf"); + if(useLocalMem){ + mLocalWorkSize = {static_cast(local_size), 1}; + }else{ + mLocalWorkSize = localWS2DDefault(mGlobalWorkSize, maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), "gemv_conv_c8_buf", unit.kernel).first; + } mOpenCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1]}; unit.localWorkSize = {mLocalWorkSize[0], mLocalWorkSize[1]}; return; } -unsigned int ConvBufLowMemoryExecution::tuneGemmLowMemory(Tensor * input, Tensor * output, std::string option, bool onlyGetTime) { - mUnits.resize(3); - unsigned int total_time = 0; +void ConvBufLowMemoryExecution::tuneGemmLowMemory(Tensor * input, Tensor * output) { + mUnits.resize(1); + auto &unit = mUnits[0]; std::vector inputShape = tensorShapeFormat(input); std::vector outputShape = tensorShapeFormat(output); - int channelPack = 16; - if(mResource->mUseImage && mResource->mNumQuantBit == 4){ - channelPack = 32; - } const int outChannel = outputShape.at(3); const int inputChannels = inputShape.at(3); const int batch = outputShape.at(0); const int width_height = outputShape.at(1) * outputShape.at(2); - const int inputChannelAlign = ROUND_UP(inputChannels, channelPack); + const int inputChannelAlign = ROUND_UP(inputChannels, 4); const int outputChannelAlign = ROUND_UP(outChannel, 4); const int blockNum = mResource->mBlockSize; const int blockDim = mResource->mInputChannel / mResource->mBlockSize; int global_y = batch * width_height; - const int total_kernel = 3; - std::string kernelName[total_kernel] = {"gemm_b4_c1_buf", "gemm_b4_c2_buf", "gemm_b4_c4_buf"}; - int itemC[total_kernel] = {1, 2, 4}; - int actual_kernel = total_kernel; - std::shared_ptr kernel[total_kernel]; - std::vector globalWorkSize[total_kernel]; - std::vector localWorkSize[total_kernel]; - std::pair min_cost(INT_MAX, 0);//(min_time, min_index) + std::string kernelName = "gemm_b4_c8"; std::set buildOption = mResource->mBuildOptions; - if(blockDim % 16 != 0){ - buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); - } else if (mResource->mUseImage && mResource->mNumQuantBit == 4 && blockDim % 32 != 0) { - // Image weight-int4 use load32 - buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + int inputChannelLeaves = 0; + int inputBatchLeaves = global_y % 4; + if(mResource->mNumQuantBit == 4){ + inputChannelLeaves = blockDim % 4; + kernelName += "_int4_buf"; + } else { + inputChannelLeaves = blockDim % 4; + kernelName += "_int8_buf"; } - buildOption.emplace(option); + buildOption.emplace("-DINPUT_CHANNEL_LEAVES_NUM=" + std::to_string(inputChannelLeaves)); + buildOption.emplace("-DINPUT_BATCH_LEAVES_NUM=" + std::to_string(inputBatchLeaves)); if(mResource->mUseImage){ buildOption.emplace("-DUSE_IMAGE"); } - std::string info = std::to_string(inputChannels) + "_" + std::to_string(outChannel) + option; - // mResource->mInputChannel ROUND_UP to blockDim, avoid gemm overstep - mConvGemmInpTensor.reset(Tensor::createDevice({ROUND_UP(batch, 4) * inputChannelAlign * width_height})); - mConvGemmOutTensor.reset(Tensor::createDevice({ROUND_UP(batch, 4) * ROUND_UP(mResource->mOutputChannel, 4) * width_height})); - mOpenCLBackend->onAcquireBuffer(mConvGemmInpTensor.get(), Backend::DYNAMIC); - mOpenCLBackend->onAcquireBuffer(mConvGemmOutTensor.get(), Backend::DYNAMIC); - mOpenCLBackend->onReleaseBuffer(mConvGemmOutTensor.get(), Backend::DYNAMIC); - mOpenCLBackend->onReleaseBuffer(mConvGemmInpTensor.get(), Backend::DYNAMIC); - - // reshape n*c/4*4*hw -> n/4*hw*c*4 - { - auto &unit = mUnits[0]; - mGlobalWorkSize = {static_cast(UP_DIV(inputChannelAlign, 4)), static_cast(UP_DIV(global_y, 4))}; - unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_conv1x1_buf", "reshape_nchw4_nhwc4", buildOption); - uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(unit.kernel)); - - uint32_t idx = 0; - cl_int ret = CL_SUCCESS; - ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]); - ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(input)); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mConvGemmInpTensor.get())); - ret |= unit.kernel->get().setArg(idx++, static_cast(global_y)); - ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannels)); - ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannelAlign)); - MNN_CHECK_CL_SUCCESS(ret, "setArg reshape_nc4_cn4"); - std::pair, unsigned int> retTune = localWS2DDefault(mGlobalWorkSize, maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), "reshape_nchw4_nhwc4", unit.kernel); - total_time += retTune.second; - mLocalWorkSize = retTune.first; - if(false == onlyGetTime){ - mOpenCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); - } - unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1]}; - unit.localWorkSize = {mLocalWorkSize[0], mLocalWorkSize[1]}; - } - // gemm - { - auto &unit = mUnits[1]; - for (int knl_idx = 0; knl_idx < actual_kernel; knl_idx++) { - kernel[knl_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_conv1x1_buf", kernelName[knl_idx], buildOption); - uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel[knl_idx])); - - globalWorkSize[knl_idx] = {static_cast(UP_DIV(outChannel, itemC[knl_idx])), static_cast(UP_DIV(global_y, 4))}; - uint32_t idx = 0; - cl_int ret = CL_SUCCESS; - ret |= kernel[knl_idx]->get().setArg(idx++, globalWorkSize[knl_idx][0]); - ret |= kernel[knl_idx]->get().setArg(idx++, globalWorkSize[knl_idx][1]); - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mConvGemmInpTensor.get())); - if(mResource->mUseImage){ - ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->mKernelImage.get()); - }else{ - ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->mKernelBuffer.get()); - } - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mConvGemmOutTensor.get())); - ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(UP_DIV(global_y, 4) * 4)); - ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(outputChannelAlign)); - ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(inputChannelAlign)); - ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(blockNum)); - ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(blockDim)); - MNN_CHECK_CL_SUCCESS(ret, "setArg gemv_conv1x1_buf Kernel Select"); - std::pair, unsigned int> retTune; - retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); - if(min_cost.first > retTune.second) { - min_cost.first = retTune.second; - min_cost.second = knl_idx; - mLocalWorkSize = {retTune.first[0], retTune.first[1]}; - } - } - total_time += min_cost.first; - int min_index = min_cost.second; - mGlobalWorkSize = {globalWorkSize[min_index][0], globalWorkSize[min_index][1]}; - - - unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_conv1x1_buf", kernelName[min_index], buildOption); - uint32_t idx = 0; - cl_int ret = CL_SUCCESS; - ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]); - ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mConvGemmInpTensor.get())); - if(mResource->mUseImage){ - ret |= unit.kernel->get().setArg(idx++, *mResource->mKernelImage.get()); - }else{ - ret |= unit.kernel->get().setArg(idx++, *mResource->mKernelBuffer.get()); - } - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mConvGemmOutTensor.get())); - ret |= unit.kernel->get().setArg(idx++, static_cast(UP_DIV(global_y, 4) * 4)); - ret |= unit.kernel->get().setArg(idx++, static_cast(outputChannelAlign)); - ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannelAlign)); - ret |= unit.kernel->get().setArg(idx++, static_cast(blockNum)); - ret |= unit.kernel->get().setArg(idx++, static_cast(blockDim)); - MNN_CHECK_CL_SUCCESS(ret, "setArg gemm_conv1x1_buf"); - if(false == onlyGetTime){ - mOpenCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); - } - unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1]}; - unit.localWorkSize = {mLocalWorkSize[0], mLocalWorkSize[1]}; - } - // reshape n/4*hw*c*4 -> n*c/4*4*hw - { - auto &unit = mUnits[2]; - mGlobalWorkSize = {static_cast(UP_DIV(mResource->mOutputChannel, 4)), static_cast(UP_DIV(global_y, 4))}; - unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_conv1x1_buf", "reshape_nhwc4_nchw4", buildOption); - uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(unit.kernel)); - uint32_t idx = 0; - cl_int ret = CL_SUCCESS; - ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]); - ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mConvGemmOutTensor.get())); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(output)); - ret |= unit.kernel->get().setArg(idx++, static_cast(global_y)); - ret |= unit.kernel->get().setArg(idx++, static_cast(outputChannelAlign)); - MNN_CHECK_CL_SUCCESS(ret, "setArg reshape_cn4_nc4"); - std::pair, unsigned int> retTune = localWS2DDefault(mGlobalWorkSize, maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), "reshape_nhwc4_nchw4", unit.kernel); - mLocalWorkSize = retTune.first; - total_time += retTune.second; - if(false == onlyGetTime){ - mOpenCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); - } - unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1]}; - unit.localWorkSize = {mLocalWorkSize[0], mLocalWorkSize[1]}; + std::string info = std::to_string(inputChannels) + "_" + std::to_string(outChannel); + + + unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_conv1x1_buf", kernelName, buildOption); + uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(unit.kernel)); + + mGlobalWorkSize = {static_cast(UP_DIV(global_y, 4)), static_cast(UP_DIV(outChannel, 8))}; + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]); + ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(input)); + if(mResource->mUseImage){ + ret |= unit.kernel->get().setArg(idx++, *mResource->mKernelImage.get()); + }else{ + ret |= unit.kernel->get().setArg(idx++, *mResource->mKernelBuffer.get()); } - return total_time; + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(output)); + ret |= unit.kernel->get().setArg(idx++, static_cast(global_y)); + ret |= unit.kernel->get().setArg(idx++, static_cast(outputChannelAlign)); + ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannelAlign)); + ret |= unit.kernel->get().setArg(idx++, static_cast(blockNum)); + ret |= unit.kernel->get().setArg(idx++, static_cast(blockDim)); + MNN_CHECK_CL_SUCCESS(ret, "setArg gemm_conv1x1_buf"); + mLocalWorkSize = localWS2DDefault(mGlobalWorkSize, maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName, unit.kernel).first; + mOpenCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); + unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1]}; + unit.localWorkSize = {mLocalWorkSize[0], mLocalWorkSize[1]}; + return; } ConvBufLowMemoryExecution::ConvBufLowMemoryExecution(const std::vector &inputs, const std::vector &outputs, const MNN::Op *op, Backend *backend) : ConvBufCommonExecution(op->main_as_Convolution2D(), backend), CommonExecution(backend, op) { @@ -804,7 +703,7 @@ ConvBufLowMemoryExecution::ConvBufLowMemoryExecution(const std::vector getInfoFromOpLowMemory(quanCommon); //select opt conv method if (mResource->mKernelHeight == mResource->mKernelWidth && mResource->mKernelHeight == 1 && mResource->mStrides[0] == 1 && mResource->mStrides[1] == 1 && conv2dCommonParams->padX() == 0 && conv2dCommonParams->padY() == 0 && conv2dCommonParams->dilateX() == 1 && conv2dCommonParams->dilateY() == 1) { - set1x1WeightLowMemory(4, 16, mFilterDataPtr, quanCommon); + set1x1WeightLowMemory(8, 4, mFilterDataPtr, quanCommon); mResource->mConv1x1Opt = true; }else { // set mFilter for not 1x1 case @@ -875,20 +774,8 @@ ErrorCode ConvBufLowMemoryExecution::onResize(const std::vector &input if(batch > 512){ useFPWeightGemmLowMemory(input, output); mUseFPWeight = true; - } - else if(false == getPreParamInfo("ConvBufLowMemoryPreArrangeMode", &batchConvMode, runTime)){ - if(tuneGemmLowMemory(input, output, "-DFORMAT_CNHW", true) < tuneGemmLowMemory(input, output, "", true)){ - batchConvMode = 1; - } else{ - batchConvMode = 2; - } - setPreParamInfo("ConvBufLowMemoryPreArrangeMode", batchConvMode, runTime); } else { - std::string option = ""; - if(1 == batchConvMode){ - option = "-DFORMAT_CNHW"; - } - tuneGemmLowMemory(input, output, option); + tuneGemmLowMemory(input, output); } } } else { diff --git a/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.hpp b/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.hpp index 5e04ac1aa..e0f3ee158 100644 --- a/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.hpp +++ b/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.hpp @@ -31,8 +31,8 @@ class ConvBufLowMemoryExecution : public ConvBufCommonExecution, public CommonEx void tuneGeneralCaseLowMemory(Tensor * input, Tensor * output); void useFPWeightGemmLowMemory(Tensor * input, Tensor * output); void tuneGemvLowMemory(Tensor * input, Tensor * output); - unsigned int tuneGemmLowMemory(Tensor * input, Tensor * output, std::string option, bool onlyGetTime = false); - bool convertToQuantWeight1x1Buffer(cl::Buffer input, int pack); + void tuneGemmLowMemory(Tensor * input, Tensor * output); + bool convertToQuantWeight1x1Buffer(cl::Buffer input, int packCin, int packCout); std::vector mPaddings{0, 0}; std::vector mGlobalWorkSize{1, 1, 1}; std::vector mLocalWorkSize{1, 1, 1, 1}; diff --git a/source/backend/opencl/execution/buffer/ConvBufWinograd.cpp b/source/backend/opencl/execution/buffer/ConvBufWinograd.cpp index bcabf60f6..fe39a9438 100644 --- a/source/backend/opencl/execution/buffer/ConvBufWinograd.cpp +++ b/source/backend/opencl/execution/buffer/ConvBufWinograd.cpp @@ -271,6 +271,18 @@ ErrorCode ConvBufWinograd::SubgroupOnResize(const std::vector &inputs, int padY = pad.second; int padX = pad.first; uint32_t total_num = input->batch(); + mUnits.resize(total_num * 3); + mMaxWGS_S.resize(total_num); + mMaxWGS_D.resize(total_num); + mMaxWGS_M.resize(total_num); + + mGWS_S.resize(total_num); + mGWS_D.resize(total_num); + mGWS_M.resize(total_num); + mLWS_S.resize(total_num); + mLWS_D.resize(total_num); + mLWS_M.resize(total_num); + auto runTime = mOpenCLBackend->getOpenCLRuntime(); std::string info = std::to_string(input->channel()) + "_" + std::to_string(output->channel()); mSource.reset(Tensor::createDevice(std::vector{alpha * alpha, UP_DIV(input->channel(), 16), ROUND_UP(wUnit * hUnit, 8), 16}, Tensor::CAFFE_C4)); @@ -448,19 +460,6 @@ ErrorCode ConvBufWinograd::onEncode(const std::vector& inputs, const st auto runTime = mOpenCLBackend->getOpenCLRuntime(); std::string info = std::to_string(input->channel()) + "_" + std::to_string(output->channel()); - - uint32_t total_num = input->batch(); - mUnits.resize(total_num * 3); - mMaxWGS_S.resize(total_num); - mMaxWGS_D.resize(total_num); - mMaxWGS_M.resize(total_num); - - mGWS_S.resize(total_num); - mGWS_D.resize(total_num); - mGWS_M.resize(total_num); - mLWS_S.resize(total_num); - mLWS_D.resize(total_num); - mLWS_M.resize(total_num); #ifdef MNN_SUPPORT_INTEL_SUBGROUP if (mResource->mUseSubgroup) { @@ -492,15 +491,41 @@ ErrorCode ConvBufWinograd::onEncode(const std::vector& inputs, const st auto icC4 = UP_DIV(input->channel(), 4); auto ocC4 = UP_DIV(output->channel(), 4); + int loop = alpha * alpha; + + int hCount = hUnit; + int wCount = wUnit; + int M_pack = ROUND_UP(wCount * hCount, mAlignM); + int K_pack = ROUND_UP(input->channel(), mAlignK); + int N_pack = ROUND_UP(output->channel(), mAlignN); + + int matmul_block_num = 1; + auto magic_ratio = 1.0 * M_pack / 1024.0 * N_pack / 1024.0 * K_pack / 1024.0; + if(magic_ratio >= 4.0) { + matmul_block_num = 16; + } else if(magic_ratio >= 2.0) { + matmul_block_num = 8; + } else if(magic_ratio >= 1.0) { + matmul_block_num = 4; + } else if(magic_ratio >= 0.5) { + matmul_block_num = 2; + } else { + matmul_block_num = 1; + } + + uint32_t batch_num = input->batch(); + uint32_t loop_num = 2 + matmul_block_num; + mUnits.resize(batch_num * loop_num); + std::set basic; /*Create Kernel*/ - for (int i = 0; i < total_num; i++) { + for (int b = 0; b < batch_num; ++b) + { char format[20]; ::memset(format, 0, sizeof(format)); sprintf(format, "%d_%d_%d", UNIT, mKernelX, INTERP); auto formatStr = std::string(format); - mUnits[i * 3].kernel = runTime->buildKernel("winogradTransform_buf", "winoTransSrcBuf" + formatStr, basic); - mMaxWGS_S[i] = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(mUnits[i * 3].kernel)); + mUnits[b * loop_num].kernel = runTime->buildKernel("winogradTransform_buf", "winoTransSrcBuf" + formatStr, basic); { std::set buildOptions = basic; if (mResource->mCommon->relu()) { @@ -509,58 +534,51 @@ ErrorCode ConvBufWinograd::onEncode(const std::vector& inputs, const st if (mResource->mCommon->relu6()) { buildOptions.emplace("-DRELU6"); } - mUnits[i * 3 + 2].kernel = runTime->buildKernel("winogradTransform_buf", "winoTransDstBuf" + formatStr, buildOptions); - mMaxWGS_D[i] = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(mUnits[i * 3 + 2].kernel)); + mUnits[b * loop_num + loop_num-1].kernel = runTime->buildKernel("winogradTransform_buf", "winoTransDstBuf" + formatStr, buildOptions); } } + auto maxWGS_S = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(mUnits[0].kernel)); + auto maxWGS_D = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(mUnits[loop_num-1].kernel)); - int hCount = hUnit; - int wCount = wUnit; - int M_pack = ROUND_UP(wCount * hCount, mAlignM); - int K_pack = ROUND_UP(input->channel(), mAlignK); - int N_pack = ROUND_UP(output->channel(), mAlignN); - for (int b = 0; b < input->batch(); ++b) { + for (int b = 0; b < batch_num; ++b) { // Source Transform { - mGWS_S[b] = {static_cast(M_pack), static_cast(UP_DIV(K_pack, 4))}; + std::vector gws_S = {static_cast(M_pack), static_cast(UP_DIV(K_pack, 4))}; + int kernel_idx = b * loop_num; int index = 0; cl_int ret = CL_SUCCESS; - ret |= mUnits[b * 3].kernel->get().setArg(index++, mGWS_S[b][0]); - ret |= mUnits[b * 3].kernel->get().setArg(index++, mGWS_S[b][1]); - ret |= mUnits[b * 3].kernel->get().setArg(index++, openCLBuffer(input)); - ret |= mUnits[b * 3].kernel->get().setArg(index++, openCLBuffer(mSource.get())); - ret |= mUnits[b * 3].kernel->get().setArg(index++, wCount); - ret |= mUnits[b * 3].kernel->get().setArg(index++, hCount); - ret |= mUnits[b * 3].kernel->get().setArg(index++, padX); - ret |= mUnits[b * 3].kernel->get().setArg(index++, padY); - ret |= mUnits[b * 3].kernel->get().setArg(index++, input->width()); - ret |= mUnits[b * 3].kernel->get().setArg(index++, input->height()); - ret |= mUnits[b * 3].kernel->get().setArg(index++, icC4); - ret |= mUnits[b * 3].kernel->get().setArg(index++, M_pack); - ret |= mUnits[b * 3].kernel->get().setArg(index++, K_pack); - ret |= mUnits[b * 3].kernel->get().setArg(index++, input->batch()); - ret |= mUnits[b * 3].kernel->get().setArg(index++, b); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, gws_S[0]); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, gws_S[1]); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, openCLBuffer(input)); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, openCLBuffer(mSource.get())); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, wCount); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, hCount); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, padX); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, padY); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, input->width()); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, input->height()); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, icC4); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, M_pack); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, K_pack); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, input->batch()); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, b); MNN_CHECK_CL_SUCCESS(ret, "setArg ConvWinogradBuf Source Trans"); std::string kernelName = "winoTransSrcBuf"; - mLWS_S[b] = localWS2DDefault(mGWS_S[b], mMaxWGS_S[b], mOpenCLBackend->getOpenCLRuntime(), kernelName + info, mUnits[b * 3].kernel).first; - mOpenCLBackend->recordKernel2d(mUnits[b * 3].kernel, mGWS_S[b], mLWS_S[b]); - mUnits[b * 3].globalWorkSize = {mGWS_S[b][0], mGWS_S[b][1]}; - mUnits[b * 3].localWorkSize = {mLWS_S[b][0], mLWS_S[b][1]}; + auto lws_S = localWS2DDefault(gws_S, maxWGS_S, mOpenCLBackend->getOpenCLRuntime(), kernelName + info, mUnits[kernel_idx].kernel).first; + mOpenCLBackend->recordKernel2d(mUnits[kernel_idx].kernel, gws_S, lws_S); + mUnits[kernel_idx].globalWorkSize = {gws_S[0], gws_S[1]}; + mUnits[kernel_idx].localWorkSize = {lws_S[0], lws_S[1]}; } // MatMul - + int each_loop = loop / matmul_block_num; + for(int block_idx = 0; block_idx < matmul_block_num; block_idx++) { - int loop = alpha * alpha; - int e_pack = ROUND_UP(wCount * hCount, mAlignM); - int l_pack = ROUND_UP(input->channel(), mAlignK); - int h_pack = ROUND_UP(output->channel(), mAlignN); - std::set buildOptions; uint32_t layout = 4; - auto param = getGemmParams({(uint32_t)e_pack, (uint32_t)h_pack, (uint32_t)l_pack, layout, (uint32_t)loop, (uint32_t)0}, {openCLBuffer(mSource.get()), openCLBuffer(mResource->mWeight.get()), openCLBuffer(mDest.get())}, mOpenCLBackend->getOpenCLRuntime()); + auto param = getGemmParams({(uint32_t)M_pack, (uint32_t)N_pack, (uint32_t)K_pack, layout, (uint32_t)each_loop, (uint32_t)0}, {openCLBuffer(mSource.get()), openCLBuffer(mResource->mWeight.get()), openCLBuffer(mDest.get())}, mOpenCLBackend->getOpenCLRuntime()); int KWG=param[0], KWI=param[1], MDIMA=param[2], MDIMC=param[3], MWG=param[4], NDIMB=param[5], NDIMC=param[6], NWG=param[7], SA=param[8], SB=param[9], STRM=param[10], STRN=param[11], VWM=param[12], VWN=param[13]; buildOptions.emplace("-DKWG=" + std::to_string(KWG)); @@ -590,72 +608,78 @@ ErrorCode ConvBufWinograd::onEncode(const std::vector& inputs, const st buildOptions.emplace("-DUSE_CL_MAD=1"); buildOptions.emplace("-DRELAX_WORKGROUP_SIZE=1"); } - - mUnits[b * 3 + 1].kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("matmul_params_buf", "XgemmBatched", buildOptions); + + int kernel_idx = b * loop_num + block_idx + 1; + mUnits[kernel_idx].kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("matmul_params_buf", "XgemmBatched", buildOptions); int out_per_thread_m = tileM / localM; int out_per_thread_n = tileN / localN; - mGWS_M[b] = {static_cast(e_pack/out_per_thread_m), static_cast(h_pack/out_per_thread_n), static_cast(loop)}; - mLWS_M[b] = {static_cast(localM), static_cast(localN), 1}; + std::vector gws_M = {static_cast(M_pack/out_per_thread_m), static_cast(N_pack/out_per_thread_n), static_cast(each_loop)}; + std::vector lws_M = {static_cast(localM), static_cast(localN), 1}; float alpha = 1.0f; float beta = 0.0f; - int batch_offset_a = e_pack * l_pack; - int batch_offset_b = h_pack * l_pack; - int batch_offset_c = e_pack * h_pack; + int batch_offset_a = M_pack * K_pack; + int batch_offset_b = N_pack * K_pack; + int batch_offset_c = M_pack * N_pack; int batch_offset[4] = {batch_offset_a, batch_offset_b, batch_offset_c, 0}; - int stride[4] = {e_pack, h_pack, h_pack, h_pack}; - int group[4] = {1, 1, 1, loop}; + int base_ptr_offset[4] = {block_idx * each_loop * batch_offset_a, \ + block_idx * each_loop * batch_offset_b, \ + block_idx * each_loop * batch_offset_c, \ + 0}; + int stride[4] = {M_pack, N_pack, N_pack, N_pack}; + int group[4] = {1, 1, 1, (int)each_loop}; int idx = 0; cl_int ret = CL_SUCCESS; - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, static_cast(e_pack)); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, static_cast(h_pack)); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, static_cast(l_pack)); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, alpha); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, beta); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, openCLBuffer(mSource.get())); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, openCLBuffer(mResource->mWeight.get())); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, openCLBuffer(mDest.get())); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, batch_offset); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, stride); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, group); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, static_cast(M_pack)); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, static_cast(N_pack)); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, static_cast(K_pack)); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, alpha); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, beta); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, openCLBuffer(mSource.get())); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, openCLBuffer(mResource->mWeight.get())); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, openCLBuffer(mDest.get())); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, batch_offset); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, base_ptr_offset); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, stride); + ret |= mUnits[kernel_idx].kernel->get().setArg(idx++, group); MNN_CHECK_CL_SUCCESS(ret, "setArg Winograd batchmatmul Kernel"); - mOpenCLBackend->recordKernel3d(mUnits[b * 3 + 1].kernel, mGWS_M[b], mLWS_M[b]); - mUnits[b * 3 + 1].globalWorkSize = {mGWS_M[b][0], mGWS_M[b][1], mGWS_M[b][2]}; - mUnits[b * 3 + 1].localWorkSize = {mLWS_M[b][0], mLWS_M[b][1], mLWS_M[b][2]}; + mOpenCLBackend->recordKernel3d(mUnits[kernel_idx].kernel, gws_M, lws_M); + mUnits[kernel_idx].globalWorkSize = {gws_M[0], gws_M[1], gws_M[2]}; + mUnits[kernel_idx].localWorkSize = {lws_M[0], lws_M[1], lws_M[2]}; } // Dest Transform { - mGWS_D[b] = {static_cast(wCount * hCount), static_cast(ocC4)}; - + std::vector gws_D = {static_cast(wCount * hCount), static_cast(ocC4)}; + int kernel_idx = b * loop_num + loop_num - 1; int index = 0; cl_int ret = CL_SUCCESS; - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, mGWS_D[b][0]); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, mGWS_D[b][1]); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, openCLBuffer(mDest.get())); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, openCLBuffer(mResource->mBias.get())); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, openCLBuffer(output)); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, wCount); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, hCount); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, output->width()); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, output->height()); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, ocC4); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, M_pack); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, N_pack); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, input->batch()); - ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, b); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, gws_D[0]); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, gws_D[1]); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, openCLBuffer(mDest.get())); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, openCLBuffer(mResource->mBias.get())); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, openCLBuffer(output)); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, wCount); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, hCount); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, output->width()); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, output->height()); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, ocC4); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, M_pack); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, N_pack); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, input->batch()); + ret |= mUnits[kernel_idx].kernel->get().setArg(index++, b); MNN_CHECK_CL_SUCCESS(ret, "setArg ConvWinogradBuf Dest Trans"); std::string kernelName = "winoTransDstBuf"; - mLWS_D[b] = localWS2DDefault(mGWS_D[b], mMaxWGS_D[b], mOpenCLBackend->getOpenCLRuntime(), kernelName + info, mUnits[b * 3 + 2].kernel).first; - mOpenCLBackend->recordKernel2d(mUnits[b * 3 + 2].kernel, mGWS_D[b], mLWS_D[b]); - mUnits[b * 3 + 2].globalWorkSize = {mGWS_D[b][0], mGWS_D[b][1]}; - mUnits[b * 3 + 2].localWorkSize = {mLWS_D[b][0], mLWS_D[b][1]}; + auto lws_D = localWS2DDefault(gws_D, maxWGS_D, mOpenCLBackend->getOpenCLRuntime(), kernelName + info, mUnits[kernel_idx].kernel).first; + mOpenCLBackend->recordKernel2d(mUnits[kernel_idx].kernel, gws_D, lws_D); + mUnits[kernel_idx].globalWorkSize = {gws_D[0], gws_D[1]}; + mUnits[kernel_idx].localWorkSize = {lws_D[0], lws_D[1]}; } } } @@ -685,11 +709,11 @@ ErrorCode ConvBufWinograd::onExecute(const std::vector &inputs, const nullptr, &event); std::string name = "Conv-winograd"; - - if(idx % 3 == 1) { - name += "-batchgemm"; - } else { + int loop_num = mUnits.size() / inputs[0]->batch(); + if(idx % loop_num == 0 || idx % loop_num == loop_num - 1) { name += "-rearrange"; + } else { + name += "-batchgemm"; } auto wUnit = UP_DIV(outputs[0]->width(), UNIT); auto hUnit = UP_DIV(outputs[0]->height(), UNIT); diff --git a/source/backend/opencl/execution/buffer/GroupNormBufExecution.cpp b/source/backend/opencl/execution/buffer/GroupNormBufExecution.cpp index 1865696ea..60915f5cf 100644 --- a/source/backend/opencl/execution/buffer/GroupNormBufExecution.cpp +++ b/source/backend/opencl/execution/buffer/GroupNormBufExecution.cpp @@ -100,8 +100,7 @@ ErrorCode GroupNormBufExecution::onEncode(const std::vector& inputs, co MNN_ASSERT(outputs.size() == 1); auto input = inputs[0]; auto output = outputs[0]; - MNN_ASSERT(input->dimensions() == 4); - MNN_ASSERT(output->dimensions() == 4); + mBatch = input->length(0); if(inputs.size() > 1) { MNN_ASSERT(inputs[1]->dimensions() == 2); diff --git a/source/backend/opencl/execution/buffer/SelfAttentionBufExecution.cpp b/source/backend/opencl/execution/buffer/SelfAttentionBufExecution.cpp index 6f4a3a97f..9206a15d6 100644 --- a/source/backend/opencl/execution/buffer/SelfAttentionBufExecution.cpp +++ b/source/backend/opencl/execution/buffer/SelfAttentionBufExecution.cpp @@ -219,6 +219,8 @@ ErrorCode SelfAttentionBufImpl::onResize(Backend *backend, const std::vectorget().setArg(idx++, openCLBuffer(mTempK.get())); ret |= mKernel_qk[seq_idx]->get().setArg(idx++, openCLBuffer(mTempQK.get())); ret |= mKernel_qk[seq_idx]->get().setArg(idx++, batch_offset); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, base_ptr_offset); ret |= mKernel_qk[seq_idx]->get().setArg(idx++, stride); ret |= mKernel_qk[seq_idx]->get().setArg(idx++, group); MNN_CHECK_CL_SUCCESS(ret, "setArg Self-Attention batchmatmul qk Kernel"); @@ -374,6 +377,7 @@ ErrorCode SelfAttentionBufImpl::onResize(Backend *backend, const std::vectorget().setArg(idx++, openCLBuffer(mTempV.get())); ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, openCLBuffer(mTempQKV.get())); ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, batch_offset); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, base_ptr_offset); ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, stride); ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, group); MNN_CHECK_CL_SUCCESS(ret, "setArg Self-Attention batchmatmul qkv Kernel"); diff --git a/source/backend/opencl/execution/cl/buffer_convert_quant.cl b/source/backend/opencl/execution/cl/buffer_convert_quant.cl index 8062b1a49..c6df69567 100644 --- a/source/backend/opencl/execution/cl/buffer_convert_quant.cl +++ b/source/backend/opencl/execution/cl/buffer_convert_quant.cl @@ -103,128 +103,124 @@ __kernel void conv2d_filter_buffer_to_nc4hw4_buffer_int4(GLOBAL_SIZE_2_DIMS } #endif -#define CHAR16_TO_UCHAR8(a, b) \ - a = (uchar8)(((b.s0 + 8) << 4) + b.s1 + 8, ((b.s2 + 8) << 4) + b.s3 + 8, ((b.s4 + 8) << 4) + b.s5 + 8, ((b.s6 + 8) << 4) + b.s7 + 8, ((b.s8 + 8) << 4) + b.s9 + 8, ((b.sa + 8) << 4) + b.sb + 8, ((b.sc + 8) << 4) + b.sd + 8, ((b.se + 8) << 4) + b.sf + 8); - -#define CHAR32_TO_UCHAR16(a, b, c) \ - a = (uchar16)(((b.s0 + 8) << 4) + b.s1 + 8, ((b.s2 + 8) << 4) + b.s3 + 8, ((b.s4 + 8) << 4) + b.s5 + 8, ((b.s6 + 8) << 4) + b.s7 + 8, ((b.s8 + 8) << 4) + b.s9 + 8, ((b.sa + 8) << 4) + b.sb + 8, ((b.sc + 8) << 4) + b.sd + 8, ((b.se + 8) << 4) + b.sf + 8, \ - ((c.s0 + 8) << 4) + c.s1 + 8, ((c.s2 + 8) << 4) + c.s3 + 8, ((c.s4 + 8) << 4) + c.s5 + 8, ((c.s6 + 8) << 4) + c.s7 + 8, ((c.s8 + 8) << 4) + c.s9 + 8, ((c.sa + 8) << 4) + c.sb + 8, ((c.sc + 8) << 4) + c.sd + 8, ((c.se + 8) << 4) + c.sf + 8); -__kernel void conv2d_1x1_weight_quant_buffer(GLOBAL_SIZE_2_DIMS -#ifdef USE_LOW_BIT_WEIGHT_INT4 - __global const uchar *input_ptr, -#else - __global const char *input_ptr, -#endif - __global char *output_ptr, - __private const int input_channel, - __private const int output_channel) { - int x = get_global_id(0); // ic / 16 - int y = get_global_id(1); // oc - - DEAL_NON_UNIFORM_DIM2(x, y); - const int xin = x << 4; - const int outputChannelC4 = (output_channel + 3) >> 2; -#ifdef USE_LOW_BIT_WEIGHT_INT4 - const int outputOffset = ((x * outputChannelC4 * 4 * 8 + y * 8)); -#ifdef CHANNEL_LEAVE - for(int i = 0; i < 8; ++i){ - int index0 = y * input_channel + xin + i * 2; - int index1 = y * input_channel + xin + i * 2 + 1; - uchar s0 = input_ptr[index0/2]; - uchar s1 = input_ptr[index1/2]; - output_ptr[outputOffset + i] = ((index0 % 2) == 0 ? (s0 & 0xf0) : (s0 << 4)) | ((index1 % 2) == 0 ? (s1 >> 4) : (s1 & 0x0f)); - } -#else - const int inputOffset = (y * input_channel + xin)/2; - vstore8(convert_char8(vload8(0,input_ptr+inputOffset)),0,output_ptr+outputOffset); -#endif -#else - const int inputOffset = y * input_channel + xin; - const int outputOffset = (x * outputChannelC4 * 4 + y) << 4; - vstore16(convert_char16(vload16(0, input_ptr + inputOffset)), 0, output_ptr + outputOffset); -#endif -} - __kernel void conv2d_1x1_weight_quant_image(GLOBAL_SIZE_2_DIMS #ifdef USE_LOW_BIT_WEIGHT_INT4 __global const uchar *input_ptr, #else - __global const uchar *input_ptr, + __global const char *input_ptr, #endif __write_only image2d_t output, __private const int input_channel, __private const int output_channel) { - int x = get_global_id(0); // ic / 32 - int y = get_global_id(1); // oc + int x = get_global_id(0); // ic / 4 + int y = get_global_id(1); // oc / 8 DEAL_NON_UNIFORM_DIM2(x, y); + const int xin = x << 2; + const int yin = y << 3; #ifdef USE_LOW_BIT_WEIGHT_INT4 - const int xin = x << 5; -#ifdef CHANNEL_LEAVE uchar16 out = 0; uchar *out_ptr = (uchar*)&out; - for(int i = 0; i < 16; ++i){ - int index0 = y * input_channel + xin + i * 2; - int index1 = y * input_channel + xin + i * 2 + 1; + for(int i = 0; i < 4; ++i){ + int index0 = yin * input_channel + xin + i; + int index1 = (yin + 1) * input_channel + xin + i; + int index2 = (yin + 2) * input_channel + xin + i; + int index3 = (yin + 3) * input_channel + xin + i; + int index4 = (yin + 4) * input_channel + xin + i; + int index5 = (yin + 5) * input_channel + xin + i; + int index6 = (yin + 6) * input_channel + xin + i; + int index7 = (yin + 7) * input_channel + xin + i; uchar s0 = input_ptr[index0/2]; uchar s1 = input_ptr[index1/2]; - out_ptr[i] = ((index0 % 2) == 0 ? (s0 & 0xf0) : (s0 << 4)) | ((index1 % 2) == 0 ? (s1 >> 4) : (s1 & 0x0f)); + uchar s2 = input_ptr[index2/2]; + uchar s3 = input_ptr[index3/2]; + uchar s4 = input_ptr[index4/2]; + uchar s5 = input_ptr[index5/2]; + uchar s6 = input_ptr[index6/2]; + uchar s7 = input_ptr[index7/2]; + out_ptr[i * 4] = ((index0 % 2) == 0 ? (s0 & 0xf0) : (s0 << 4)) | ((index1 % 2) == 0 ? (s1 >> 4) : (s1 & 0x0f)); + out_ptr[i * 4 + 1] = ((index2 % 2) == 0 ? (s2 & 0xf0) : (s2 << 4)) | ((index3 % 2) == 0 ? (s3 >> 4) : (s3 & 0x0f)); + out_ptr[i * 4 + 2] = ((index4 % 2) == 0 ? (s4 & 0xf0) : (s4 << 4)) | ((index5 % 2) == 0 ? (s5 >> 4) : (s5 & 0x0f)); + out_ptr[i * 4 + 3] = ((index6 % 2) == 0 ? (s6 & 0xf0) : (s6 << 4)) | ((index7 % 2) == 0 ? (s7 >> 4) : (s7 & 0x0f)); } - write_imagei(output, (int2)(y, x), as_int4(out)); + write_imagei(output, (int2)(x, y), as_int4(out)); #else - const int inputOffset = (y * input_channel + xin)/2; - write_imagei(output, (int2)(y, x), as_int4(vload16(0, input_ptr + inputOffset))); -#endif -#else - const int xin = x << 4; - const int inputOffset = y * input_channel + xin; - write_imagei(output, (int2)(y, x), as_int4(vload16(0, input_ptr + inputOffset))); + const int inputOffset = yin * input_channel + xin; + char4 s0 = vload4(0, input_ptr + inputOffset); + char4 s1 = vload4(0, input_ptr + inputOffset + input_channel); + char4 s2 = vload4(0, input_ptr + inputOffset + input_channel * 2); + char4 s3 = vload4(0, input_ptr + inputOffset + input_channel * 3); + char4 s4 = vload4(0, input_ptr + inputOffset + input_channel * 4); + char4 s5 = vload4(0, input_ptr + inputOffset + input_channel * 5); + char4 s6 = vload4(0, input_ptr + inputOffset + input_channel * 6); + char4 s7 = vload4(0, input_ptr + inputOffset + input_channel * 7); + char16 out0 = (char16)(s0.s0, s1.s0, s2.s0, s3.s0, s4.s0, s5.s0, s6.s0, s7.s0, s0.s1, s1.s1, s2.s1, s3.s1, s4.s1, s5.s1, s6.s1, s7.s1); + char16 out1 = (char16)(s0.s2, s1.s2, s2.s2, s3.s2, s4.s2, s5.s2, s6.s2, s7.s2, s0.s3, s1.s3, s2.s3, s3.s3, s4.s3, s5.s3, s6.s3, s7.s3); + write_imagei(output, (int2)(x * 2, y), as_int4(out0)); + write_imagei(output, (int2)(x * 2 + 1, y), as_int4(out1)); #endif } -__kernel void conv2d_1x1_ic_oc_weight_quant_buffer(GLOBAL_SIZE_2_DIMS +__kernel void conv2d_1x1_weight_quant_buffer(GLOBAL_SIZE_2_DIMS #ifdef USE_LOW_BIT_WEIGHT_INT4 __global const uchar *input_ptr, - __global uchar *output_ptr, //(Ci/packCin， Co/packCout, packCin， packCout) #else __global const char *input_ptr, - __global char *output_ptr, //(Ci/packCin， Co/packCout, packCin， packCout) #endif + __global char *output_ptr, __private const int input_channel, - __private const int output_channel, - __private const int icPack, - __private const int ocPack) { - int x = get_global_id(0); // ic / icPack - int y = get_global_id(1); // oc / ocPack + __private const int output_channel) { + int x = get_global_id(0); // ic / 4 + int y = get_global_id(1); // oc / 8 DEAL_NON_UNIFORM_DIM2(x, y); - const int xin = x * icPack; - const int yin = y * ocPack; - const int inputChannelC4 = (input_channel + icPack - 1) / icPack; - const int outputChannelC4 = (output_channel + ocPack - 1) / ocPack; + const int xin = x << 2; + const int yin = y << 3; + const int outputChannelC8 = (output_channel + 7) >> 3; + const int inputChannelC4 = (input_channel + 3) >> 2; #ifdef USE_LOW_BIT_WEIGHT_INT4 - const int inputOffset = (yin * input_channel + xin) / 2; - const int outputOffset = ((x * outputChannelC4 + y) * icPack * ocPack) / 2; - for(int i = 0; i < icPack; ++i){ - for(int j = 0; j < ocPack / 2; ++j){ - int index0 = (yin + j * 2) * input_channel + xin + i; - int index1 = (yin + j * 2 + 1) * input_channel + xin + i; - uchar s0 = input_ptr[index0/2]; - uchar s1 = input_ptr[index1/2]; - s0 = (index0 % 2) == 0 ? (s0 & 0xf0) : ((s0 & 0x0f) << 4); - s1 = (index1 % 2) == 0 ? (s1 >> 4) : (s1 & 0x0f); - output_ptr[outputOffset + i * (ocPack / 2) + j] = s0 | s1; - } + uchar16 out = 0; + uchar *out_ptr = (uchar*)&out; + for(int i = 0; i < 4; ++i){ + int index0 = yin * input_channel + xin + i; + int index1 = (yin + 1) * input_channel + xin + i; + int index2 = (yin + 2) * input_channel + xin + i; + int index3 = (yin + 3) * input_channel + xin + i; + int index4 = (yin + 4) * input_channel + xin + i; + int index5 = (yin + 5) * input_channel + xin + i; + int index6 = (yin + 6) * input_channel + xin + i; + int index7 = (yin + 7) * input_channel + xin + i; + uchar s0 = input_ptr[index0/2]; + uchar s1 = input_ptr[index1/2]; + uchar s2 = input_ptr[index2/2]; + uchar s3 = input_ptr[index3/2]; + uchar s4 = input_ptr[index4/2]; + uchar s5 = input_ptr[index5/2]; + uchar s6 = input_ptr[index6/2]; + uchar s7 = input_ptr[index7/2]; + out_ptr[i * 4] = ((index0 % 2) == 0 ? (s0 & 0xf0) : (s0 << 4)) | ((index1 % 2) == 0 ? (s1 >> 4) : (s1 & 0x0f)); + out_ptr[i * 4 + 1] = ((index2 % 2) == 0 ? (s2 & 0xf0) : (s2 << 4)) | ((index3 % 2) == 0 ? (s3 >> 4) : (s3 & 0x0f)); + out_ptr[i * 4 + 2] = ((index4 % 2) == 0 ? (s4 & 0xf0) : (s4 << 4)) | ((index5 % 2) == 0 ? (s5 >> 4) : (s5 & 0x0f)); + out_ptr[i * 4 + 3] = ((index6 % 2) == 0 ? (s6 & 0xf0) : (s6 << 4)) | ((index7 % 2) == 0 ? (s7 >> 4) : (s7 & 0x0f)); } + const int outputOffset = (y * inputChannelC4 + x) * 16; + vstore16(as_char16(out),0,output_ptr+outputOffset); #else const int inputOffset = yin * input_channel + xin; - const int outputOffset = (x * outputChannelC4 + y) * icPack * ocPack; - for(int i = 0; i < icPack; ++i){ - for(int j = 0; j < ocPack; ++j){ - output_ptr[outputOffset + i * ocPack + j] = input_ptr[inputOffset + j * input_channel + i]; - } - } + char4 s0 = vload4(0, input_ptr + inputOffset); + char4 s1 = vload4(0, input_ptr + inputOffset + input_channel); + char4 s2 = vload4(0, input_ptr + inputOffset + input_channel * 2); + char4 s3 = vload4(0, input_ptr + inputOffset + input_channel * 3); + char4 s4 = vload4(0, input_ptr + inputOffset + input_channel * 4); + char4 s5 = vload4(0, input_ptr + inputOffset + input_channel * 5); + char4 s6 = vload4(0, input_ptr + inputOffset + input_channel * 6); + char4 s7 = vload4(0, input_ptr + inputOffset + input_channel * 7); + char16 out0 = (char16)(s0.s0, s1.s0, s2.s0, s3.s0, s4.s0, s5.s0, s6.s0, s7.s0, s0.s1, s1.s1, s2.s1, s3.s1, s4.s1, s5.s1, s6.s1, s7.s1); + char16 out1 = (char16)(s0.s2, s1.s2, s2.s2, s3.s2, s4.s2, s5.s2, s6.s2, s7.s2, s0.s3, s1.s3, s2.s3, s3.s3, s4.s3, s5.s3, s6.s3, s7.s3); + const int outputOffset = (y * inputChannelC4 + x) * 8 * 4; + vstore16(out0, 0, output_ptr + outputOffset); + vstore16(out1, 0, output_ptr + outputOffset + 16); #endif } diff --git a/source/backend/opencl/execution/cl/conv_2d_buf.cl b/source/backend/opencl/execution/cl/conv_2d_buf.cl index 744324e14..2c25586b4 100644 --- a/source/backend/opencl/execution/cl/conv_2d_buf.cl +++ b/source/backend/opencl/execution/cl/conv_2d_buf.cl @@ -645,13 +645,16 @@ void conv_2d_c4h1w1(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int out_c_base_index +) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h DEAL_NON_UNIFORM_DIM2(out_c_w_idx, out_b_h_idx); - const int out_c_idx = out_c_w_idx / out_hw.y; + const int out_c_idx = out_c_w_idx / out_hw.y + out_c_base_index; + if(out_c_idx >= out_c_blocks) return; const int out_w_idx = out_c_w_idx % out_hw.y; const int out_b_idx = out_b_h_idx / out_hw.x;//equal to in_b_idx const int out_h_idx = out_b_h_idx % out_hw.x; @@ -725,13 +728,16 @@ void conv_2d_c4h1w2(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks,//generate width's num __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int out_c_base_index +) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h DEAL_NON_UNIFORM_DIM2(out_c_w_idx, out_b_h_idx); - const int out_c_idx = out_c_w_idx / out_w_blocks; + const int out_c_idx = out_c_w_idx / out_w_blocks + out_c_base_index; + if(out_c_idx >= out_c_blocks) return; const int out_w_idx = (out_c_w_idx % out_w_blocks) << 1; const int out_b_idx = out_b_h_idx / out_hw.x;//equal to in_b_idx const int out_h_idx = out_b_h_idx % out_hw.x; @@ -820,13 +826,16 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int out_c_base_index +) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h DEAL_NON_UNIFORM_DIM2(out_c_w_idx, out_b_h_idx); - const int out_c_idx = out_c_w_idx / out_w_blocks; + const int out_c_idx = out_c_w_idx / out_w_blocks + out_c_base_index; + if(out_c_idx >= out_c_blocks) return; const int out_w_idx = (out_c_w_idx % out_w_blocks) << 2; const int out_b_idx = out_b_h_idx / out_hw.x;//equal to in_b_idx const int out_h_idx = out_b_h_idx % out_hw.x; @@ -946,13 +955,16 @@ void conv_2d_c4h4w1(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int out_c_base_index +) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h DEAL_NON_UNIFORM_DIM2(out_c_w_idx, out_b_h_idx); - const int out_c_idx = out_c_w_idx / out_w_blocks; + const int out_c_idx = out_c_w_idx / out_w_blocks + out_c_base_index; + if(out_c_idx >= out_c_blocks) return; const int out_w_idx = out_c_w_idx % out_w_blocks; const int out_b_idx = out_b_h_idx / out_h_blocks;//equal to in_b_idx const int out_h_idx = (out_b_h_idx % out_h_blocks) << 2; @@ -1079,13 +1091,16 @@ void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int out_c_base_index +) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h DEAL_NON_UNIFORM_DIM2(out_c_w_idx, out_b_h_idx); - const int out_c_idx_0 = (out_c_w_idx / out_w_blocks) << 1; + const int out_c_idx_0 = ((out_c_w_idx / out_w_blocks + out_c_base_index) << 1); + if(out_c_idx_0 >= out_c_blocks) return; const int out_c_idx_1 = out_c_idx_0 + 1; const int out_w_idx = out_c_w_idx % out_w_blocks; const int out_b_idx = out_b_h_idx / out_h_blocks;//equal to in_b_idx @@ -1293,13 +1308,16 @@ void conv_2d_c8h2w1(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int out_c_base_index +) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h DEAL_NON_UNIFORM_DIM2(out_c_w_idx, out_b_h_idx); - const int out_c_idx_0 = (out_c_w_idx / out_w_blocks) << 1; + const int out_c_idx_0 = (out_c_w_idx / out_w_blocks + out_c_base_index) << 1; + if(out_c_idx_0 >= out_c_blocks) return; const int out_c_idx_1 = out_c_idx_0 + 1; const int out_w_idx = out_c_w_idx % out_w_blocks; const int out_b_idx = out_b_h_idx / out_h_blocks;//equal to in_b_idx @@ -1446,13 +1464,16 @@ void conv_2d_c8h1w4(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int out_c_base_index +) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h DEAL_NON_UNIFORM_DIM2(out_c_w_idx, out_b_h_idx); - const int out_c_idx_0 = (out_c_w_idx / out_w_blocks) << 1; + const int out_c_idx_0 = (out_c_w_idx / out_w_blocks + out_c_base_index) << 1; + if(out_c_idx_0 >= out_c_blocks) return; const int out_c_idx_1 = out_c_idx_0 + 1; const int out_w_idx = (out_c_w_idx % out_w_blocks) << 2; const int out_b_idx = out_b_h_idx / out_hw.x;//equal to in_b_idx diff --git a/source/backend/opencl/execution/cl/gemm_conv1x1_buf.cl b/source/backend/opencl/execution/cl/gemm_conv1x1_buf.cl index 35304f433..b8c503107 100644 --- a/source/backend/opencl/execution/cl/gemm_conv1x1_buf.cl +++ b/source/backend/opencl/execution/cl/gemm_conv1x1_buf.cl @@ -10,64 +10,10 @@ return; \ } -#define GLOBAL_SIZE_DIM3 \ - __private int global_size_dim0, __private int global_size_dim1, __private int global_size_dim2, - -#define UNIFORM_BOUNDRY_CHECK3(index0, index1, index2) \ - if(index0 >= global_size_dim0 || index1 >= global_size_dim1 || index2 >= global_size_dim2) { \ - return; \ - } - -#define UCHAR16_TO_2CHAR16(a, b, c) \ - a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; \ - a.s8 = (c.s4 >> 4) - 8; a.s9 = (c.s4 & 15) - 8; a.sa = (c.s5 >> 4) - 8; a.sb = (c.s5 & 15) - 8; a.sc = (c.s6 >> 4) - 8; a.sd = (c.s6 & 15) - 8; a.se = (c.s7 >> 4) - 8; a.sf = (c.s7 & 15) - 8; \ - b.s0 = (c.s8 >> 4) - 8; b.s1 = (c.s8 & 15) - 8; b.s2 = (c.s9 >> 4) - 8; b.s3 = (c.s9 & 15) - 8; b.s4 = (c.sa >> 4) - 8; b.s5 = (c.sa & 15) - 8; b.s6 = (c.sb >> 4) - 8; b.s7 = (c.sb & 15) - 8; \ - b.s8 = (c.sc >> 4) - 8; b.s9 = (c.sc & 15) - 8; b.sa = (c.sd >> 4) - 8; b.sb = (c.sd & 15) - 8; b.sc = (c.se >> 4) - 8; b.sd = (c.se & 15) - 8; b.se = (c.sf >> 4) - 8; b.sf = (c.sf & 15) - 8; - -#define UCHAR8_TO_CHAR16(a, c) \ - a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; \ - a.s8 = (c.s4 >> 4) - 8; a.s9 = (c.s4 & 15) - 8; a.sa = (c.s5 >> 4) - 8; a.sb = (c.s5 & 15) - 8; a.sc = (c.s6 >> 4) - 8; a.sd = (c.s6 & 15) - 8; a.se = (c.s7 >> 4) - 8; a.sf = (c.s7 & 15) - 8; - -#define DOT16X16(a, b, c) \ - c += dot(a.s0123, b.s0123); \ - c += dot(a.s4567, b.s4567); \ - c += dot(a.s89ab, b.s89ab); \ - c += dot(a.scdef, b.scdef); - -#if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) -#define CHANNEL_PACK 32 -#else -#define CHANNEL_PACK 16 -#endif - -#if (defined USE_LOW_BIT_WEIGHT_INT8) -#define WEIGHT_STRIDE 16 -#elif (defined USE_LOW_BIT_WEIGHT_INT4) -#define WEIGHT_STRIDE 8 -#endif +#define UCHAR4_TO_CHAR8(a, c) \ + a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; __constant sampler_t SAMPLER = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST; -#ifdef USE_IMAGE -inline COMPUTE_FLOAT16 readWeight(__read_only image2d_t weight, int ix, int iy, COMPUTE_FLOAT scale, COMPUTE_FLOAT offset){ - return CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(ix, iy)))) * scale + offset; -} -#else - -#if (defined USE_LOW_BIT_WEIGHT_INT8) -inline COMPUTE_FLOAT16 readWeight(__global const char *weight, int ix, int iy, COMPUTE_FLOAT scale, COMPUTE_FLOAT offset){ - return CONVERT_COMPUTE_FLOAT16(vload16(0, weight)) * scale + offset; -} -#elif (defined USE_LOW_BIT_WEIGHT_INT4) -inline COMPUTE_FLOAT16 readWeight(__global const uchar *weight, int ix, int iy, COMPUTE_FLOAT scale, COMPUTE_FLOAT offset){ - uchar16 charWeightsInt40 = vload16(0, weight); - uchar8 charWeightsInt4 = vload8(0, weight); - char16 charWeights = 0; - UCHAR8_TO_CHAR16(charWeights, charWeightsInt4); - return CONVERT_COMPUTE_FLOAT16(charWeights) * scale + offset; -} -#endif -#endif - __kernel void inverse_quant_weight(GLOBAL_SIZE_DIM2 #ifdef USE_IMAGE __read_only image2d_t weight, @@ -80,6 +26,7 @@ __kernel void inverse_quant_weight(GLOBAL_SIZE_DIM2 #endif __global const float *dequantScaleOffset, __global FLOAT* output, + __private const int inputChannel4Align, __private const int outputChannelAlign, __private const int outputChannel4Align, __private const int blockDim){ @@ -87,674 +34,627 @@ __kernel void inverse_quant_weight(GLOBAL_SIZE_DIM2 const int y = get_global_id(1); //oc UNIFORM_BOUNDRY_CHECK(x, y); - #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) - const int ic = x << 5; - const int oc = y << 2; +#if (defined USE_LOW_BIT_WEIGHT_INT4) + const int ic = x << 2; + const int oc = y << 3; const int output_offset = ic * outputChannelAlign + oc; int kindex = (ic / blockDim) * outputChannel4Align * 2; - COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(0, dequantScaleOffset + kindex + oc * 2)); - COMPUTE_FLOAT16 weights00, weights01, weights10, weights11, weights20, weights21, weights30, weights31; + COMPUTE_FLOAT8 scale, offset; { - uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(oc, x))); - uchar16 charWeightsInt41 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(oc + 1, x))); - uchar16 charWeightsInt42 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(oc + 2, x))); - uchar16 charWeightsInt43 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(oc + 3, x))); - char16 charWeights0, charWeights1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights00 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; - weights01 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); - weights10 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; - weights11 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt42); - weights20 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s4 + ScaleOffset.s5; - weights21 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s4 + ScaleOffset.s5; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt43); - weights30 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s6 + ScaleOffset.s7; - weights31 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s6 + ScaleOffset.s7; + COMPUTE_FLOAT16 ScaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + kindex + oc * 2)); + scale = ScaleOffset.s02468ace; + offset = ScaleOffset.s13579bdf; } - COMPUTE_FLOAT *weights00_ptr = (COMPUTE_FLOAT *)&weights00; - COMPUTE_FLOAT *weights10_ptr = (COMPUTE_FLOAT *)&weights10; - COMPUTE_FLOAT *weights20_ptr = (COMPUTE_FLOAT *)&weights20; - COMPUTE_FLOAT *weights30_ptr = (COMPUTE_FLOAT *)&weights30; - COMPUTE_FLOAT *weights01_ptr = (COMPUTE_FLOAT *)&weights01; - COMPUTE_FLOAT *weights11_ptr = (COMPUTE_FLOAT *)&weights11; - COMPUTE_FLOAT *weights21_ptr = (COMPUTE_FLOAT *)&weights21; - COMPUTE_FLOAT *weights31_ptr = (COMPUTE_FLOAT *)&weights31; - #pragma unroll - for (int i = 0; i < 16; ++i){ - FLOAT4 out = CONVERT_FLOAT4((COMPUTE_FLOAT4)(weights00_ptr[i], weights10_ptr[i], weights20_ptr[i], weights30_ptr[i])); - vstore4(out, 0, output+output_offset+i*outputChannelAlign); - } - #pragma unroll - for (int i = 0; i < 16; ++i){ - FLOAT4 out = CONVERT_FLOAT4((COMPUTE_FLOAT4)(weights01_ptr[i], weights11_ptr[i], weights21_ptr[i], weights31_ptr[i])); - vstore4(out, 0, output+output_offset+(i + 16)*outputChannelAlign); + COMPUTE_FLOAT8 weights0, weights1, weights2, weights3; + { + #ifdef USE_IMAGE + uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(x, y))); + #else + uchar16 charWeightsInt40 = vload16(x, weight + y * inputChannel4Align * 4); + #endif + char8 charWeights0; + UCHAR4_TO_CHAR8(charWeights0, charWeightsInt40.s0123); + weights0 = CONVERT_COMPUTE_FLOAT8(charWeights0) * scale + offset; + + UCHAR4_TO_CHAR8(charWeights0, charWeightsInt40.s4567); + weights1 = CONVERT_COMPUTE_FLOAT8(charWeights0) * scale + offset; + + UCHAR4_TO_CHAR8(charWeights0, charWeightsInt40.s89ab); + weights2 = CONVERT_COMPUTE_FLOAT8(charWeights0) * scale + offset; + + UCHAR4_TO_CHAR8(charWeights0, charWeightsInt40.scdef); + weights3 = CONVERT_COMPUTE_FLOAT8(charWeights0) * scale + offset; } - #else - const int ic = x << 4; - const int oc = y << 2; -#ifndef USE_IMAGE - #if (defined USE_LOW_BIT_WEIGHT_INT4) - int weight_offset = oc * 8; - int weight_oc_offset = outputChannel4Align * 8; - int weight_stride = 8; - #else - int weight_offset = oc * 16; - int weight_oc_offset = outputChannel4Align * 16; - int weight_stride = 16; - #endif -#endif + vstore8(weights0, 0, output+output_offset); + vstore8(weights1, 0, output+output_offset+outputChannelAlign); + vstore8(weights2, 0, output+output_offset+2*outputChannelAlign); + vstore8(weights3, 0, output+output_offset+3*outputChannelAlign); +#else + const int ic = x << 1; + const int oc = y << 3; const int output_offset = ic * outputChannelAlign + oc; int kindex = (ic / blockDim) * outputChannel4Align * 2; - COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(0, dequantScaleOffset + kindex + oc * 2)); - #ifdef USE_IMAGE - COMPUTE_FLOAT16 weights0 = readWeight(weight, oc, x, ScaleOffset.s0, ScaleOffset.s1); - COMPUTE_FLOAT16 weights1 = readWeight(weight, oc + 1, x, ScaleOffset.s2, ScaleOffset.s3); - COMPUTE_FLOAT16 weights2 = readWeight(weight, oc + 2, x, ScaleOffset.s4, ScaleOffset.s5); - COMPUTE_FLOAT16 weights3 = readWeight(weight, oc + 3, x, ScaleOffset.s6, ScaleOffset.s7); - #else - COMPUTE_FLOAT16 weights0 = readWeight(weight + weight_offset + x * weight_oc_offset, 0, 0, ScaleOffset.s0, ScaleOffset.s1); - COMPUTE_FLOAT16 weights1 = readWeight(weight + weight_offset + x * weight_oc_offset + weight_stride, 0, 0, ScaleOffset.s2, ScaleOffset.s3); - COMPUTE_FLOAT16 weights2 = readWeight(weight + weight_offset + x * weight_oc_offset + 2 * weight_stride, 0, 0, ScaleOffset.s4, ScaleOffset.s5); - COMPUTE_FLOAT16 weights3 = readWeight(weight + weight_offset + x * weight_oc_offset + 3 * weight_stride, 0, 0, ScaleOffset.s6, ScaleOffset.s7); - #endif - COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT*)&weights0; - COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT*)&weights1; - COMPUTE_FLOAT *weights2_ptr = (COMPUTE_FLOAT*)&weights2; - COMPUTE_FLOAT *weights3_ptr = (COMPUTE_FLOAT*)&weights3; - #pragma unroll - for (int i = 0; i < 16; ++i){ - FLOAT4 out = CONVERT_FLOAT4((COMPUTE_FLOAT4)(weights0_ptr[i], weights1_ptr[i], weights2_ptr[i], weights3_ptr[i])); - vstore4(out, 0, output+output_offset+i*outputChannelAlign); + COMPUTE_FLOAT8 scale, offset; + { + COMPUTE_FLOAT16 ScaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + kindex + oc * 2)); + scale = ScaleOffset.s02468ace; + offset = ScaleOffset.s13579bdf; } - #endif -} - -__kernel void reshape_nchw4_nhwc4(GLOBAL_SIZE_DIM2 -__global const FLOAT* input, -__global FLOAT* output, -__private const int bhw, -__private const int channel, -__private const int channelAlign){ - const int x = get_global_id(0); //c - const int y = get_global_id(1); //bhw - - UNIFORM_BOUNDRY_CHECK(x, y); - - const int x4 = x << 2; - const int y4 = y << 2; - const int input_offset = (x * bhw + y4) * 4; - FLOAT4 in0 = vload4(0, input + input_offset); - FLOAT4 in1 = (y4 + 1 < bhw) ? vload4(0, input + input_offset + 4) : (FLOAT4)0; - FLOAT4 in2 = (y4 + 2 < bhw) ? vload4(0, input + input_offset + 8) : (FLOAT4)0; - FLOAT4 in3 = (y4 + 3 < bhw) ? vload4(0, input + input_offset + 12) : (FLOAT4)0; - -#ifdef INPUT_CHANNEL_LEAVE - if(x4 + 3 >= channel){ - FLOAT *in0_ptr = (FLOAT*)&in0; - FLOAT *in1_ptr = (FLOAT*)&in1; - FLOAT *in2_ptr = (FLOAT*)&in2; - FLOAT *in3_ptr = (FLOAT*)&in3; - int remain = x4 + 3 - channel; - for(int i = remain; i >= 0; i--){ - in0_ptr[3 - i] = 0; - in1_ptr[3 - i] = 0; - in2_ptr[3 - i] = 0; - in3_ptr[3 - i] = 0; - } + COMPUTE_FLOAT8 weights0, weights1; + { + #ifdef USE_IMAGE + COMPUTE_FLOAT16 wei = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(x, y)))); + #else + COMPUTE_FLOAT16 wei = CONVERT_COMPUTE_FLOAT16(vload16(x, weight + y * inputChannel4Align * 8)); + #endif + weights0 = wei.s01234567 * scale + offset; + weights1 = wei.s89abcdef * scale + offset; } -#endif - -#ifdef FORMAT_CNHW - int idx = x / 4; - int idy = x % 4; - const int bhw4 = (bhw + 3) / 4 * 4; - int output_offset = ((idx * bhw4 + y4) * 4 + idy) * 4; // [c/16 b 4 4] - vstore4(in0, 0, output+output_offset); - vstore4(in1, 0, output+output_offset+16); - vstore4(in2, 0, output+output_offset+32); - vstore4(in3, 0, output+output_offset+48); -#else - FLOAT16 out = (FLOAT16)(in0.s0, in1.s0, in2.s0, in3.s0, in0.s1, in1.s1, in2.s1, in3.s1, in0.s2, in1.s2, in2.s2, in3.s2, in0.s3, in1.s3, in2.s3, in3.s3); - const int output_offset = (y * channelAlign + x4) * 4; - vstore16(out, 0, output+output_offset); + vstore8(weights0, 0, output+output_offset); + vstore8(weights1, 0, output+output_offset+outputChannelAlign); #endif } -__kernel void reshape_nhwc4_nchw4(GLOBAL_SIZE_DIM2 -__global const FLOAT* input, -__global FLOAT* output, -__private const int bhw, -__private const int channelAlign){ - const int x = get_global_id(0); //c - const int y = get_global_id(1); //bhw - - UNIFORM_BOUNDRY_CHECK(x, y); - - const int x4 = x << 2; - const int y4 = y << 2; - const int output_offset = (x * bhw + y4) * 4; - +#define UCHAR4_TO_FLOAT8(b, scale, offset) \ + wei.s0 = (COMPUTE_FLOAT)((b.s0 >> 4) - 8); \ + wei.s1 = (COMPUTE_FLOAT)((b.s0 & 15) - 8); \ + wei.s2 = (COMPUTE_FLOAT)((b.s1 >> 4) - 8); \ + wei.s3 = (COMPUTE_FLOAT)((b.s1 & 15) - 8); \ + wei.s4 = (COMPUTE_FLOAT)((b.s2 >> 4) - 8); \ + wei.s5 = (COMPUTE_FLOAT)((b.s2 & 15) - 8); \ + wei.s6 = (COMPUTE_FLOAT)((b.s3 >> 4) - 8); \ + wei.s7 = (COMPUTE_FLOAT)((b.s3 & 15) - 8); \ + wei = wei * scale + offset; - const int input_offset = (y * channelAlign + x4) * 4; - FLOAT16 in = vload16(0, input + input_offset); - - FLOAT4 out0 = (FLOAT4)(in.s0, in.s4, in.s8, in.sc); - FLOAT4 out1 = (FLOAT4)(in.s1, in.s5, in.s9, in.sd); - FLOAT4 out2 = (FLOAT4)(in.s2, in.s6, in.sa, in.se); - FLOAT4 out3 = (FLOAT4)(in.s3, in.s7, in.sb, in.sf); - vstore4(out0, 0, output+output_offset); - if(y4 + 1 >= bhw) return; - vstore4(out1, 0, output+output_offset+4); - if(y4 + 2 >= bhw) return; - vstore4(out2, 0, output+output_offset+8); - if(y4 + 3 >= bhw) return; - vstore4(out3, 0, output+output_offset+12); -} - - -__kernel void gemm_b4_c4_buf(GLOBAL_SIZE_DIM2 +__kernel void gemm_b4_c8_int4_buf(GLOBAL_SIZE_DIM2 __global const FLOAT* input, #ifdef USE_IMAGE __read_only image2d_t weight, #else -#if (defined USE_LOW_BIT_WEIGHT_INT8) - __global const char *weight, -#elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *weight, -#endif #endif __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT* output, - __private const int bhw4, + __private const int bhw, __private const int dstChannelAlign, __private const int srcChannelAlign, __private const int blockNum, __private const int blockDim) { - const int x = get_global_id(0); //c - const int y = get_global_id(1); //b + const int x = get_global_id(0); //b/4 + const int y = get_global_id(1); //c/8 UNIFORM_BOUNDRY_CHECK(x, y); + + const int out_b_idx = x << 2; + const int out_c_idx = y << 1; - const int out_c_idx = x << 2; - const int out_b_idx = y << 2; - - COMPUTE_FLOAT4 bias0 = CONVERT_COMPUTE_FLOAT4(vload4(0, bias + out_c_idx)); - COMPUTE_FLOAT4 out = (COMPUTE_FLOAT4)bias0.s0; - COMPUTE_FLOAT4 out1 = (COMPUTE_FLOAT4)bias0.s1, out2 = (COMPUTE_FLOAT4)bias0.s2, out3 = (COMPUTE_FLOAT4)bias0.s3; - -#ifdef FORMAT_CNHW - int input_offset = out_b_idx * 16; -#else - int input_offset = out_b_idx * srcChannelAlign; -#endif - int out_offset = out_b_idx * dstChannelAlign + out_c_idx * 4; + COMPUTE_FLOAT8 out0 = CONVERT_FLOAT8(vload8(0, bias + (out_c_idx << 2))); + COMPUTE_FLOAT8 out1 = out0; + COMPUTE_FLOAT8 out2 = out0; + COMPUTE_FLOAT8 out3 = out0; + const int bhw4 = bhw << 2; + const int input_offset = out_b_idx * 4; + int out_offset = out_c_idx * bhw4 + out_b_idx * 4; #ifndef USE_IMAGE - int weight_offset = out_c_idx * WEIGHT_STRIDE; - int weight_oc_offset = dstChannelAlign * WEIGHT_STRIDE; + const int weight_offset = y * srcChannelAlign * 4; +#endif + const int loop = (blockDim + 4 - 1) / 4; +#if INPUT_CHANNEL_LEAVES_NUM != 0 + const int loop_end = max(loop - 1, 0); +#else + const int loop_end = loop; #endif - const int loop = (blockDim + CHANNEL_PACK - 1) / CHANNEL_PACK; - - for (int i = 0; i < blockNum; i++){ - int kindex = i * dstChannelAlign * 2; - COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(0, dequantScaleOffset + kindex + out_c_idx * 2)); - for (int j = 0; j < loop; j++) { - int k = i * loop + j; - #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) - COMPUTE_FLOAT16 weights00, weights01, weights10, weights11, weights20, weights21, weights30, weights31; +#if INPUT_BATCH_LEAVES_NUM != 0 + if(out_b_idx + 3 >= bhw){ + for (int i = 0; i < blockNum; i++){ + COMPUTE_FLOAT8 scale, offset; { - uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); - uchar16 charWeightsInt41 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 1, k))); - uchar16 charWeightsInt42 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 2, k))); - uchar16 charWeightsInt43 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 3, k))); - char16 charWeights0, charWeights1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights00 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; - weights01 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); - weights10 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; - weights11 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt42); - weights20 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s4 + ScaleOffset.s5; - weights21 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s4 + ScaleOffset.s5; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt43); - weights30 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s6 + ScaleOffset.s7; - weights31 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s6 + ScaleOffset.s7; + COMPUTE_FLOAT16 scaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + (out_c_idx << 3) + i * dstChannelAlign * 2)); + scale = scaleOffset.s02468ace; + offset = scaleOffset.s13579bdf; } - #ifdef FORMAT_CNHW - int k2 = k << 1; - COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16)); - DOT16X16(in, weights00, out.s0); - DOT16X16(in, weights10, out1.s0); - DOT16X16(in, weights20, out2.s0); - DOT16X16(in, weights30, out3.s0); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16 + 16)); - DOT16X16(in, weights00, out.s1); - DOT16X16(in, weights10, out1.s1); - DOT16X16(in, weights20, out2.s1); - DOT16X16(in, weights30, out3.s1); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16 + 32)); - DOT16X16(in, weights00, out.s2); - DOT16X16(in, weights10, out1.s2); - DOT16X16(in, weights20, out2.s2); - DOT16X16(in, weights30, out3.s2); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16 + 48)); - DOT16X16(in, weights00, out.s3); - DOT16X16(in, weights10, out1.s3); - DOT16X16(in, weights20, out2.s3); - DOT16X16(in, weights30, out3.s3); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16)); - DOT16X16(in, weights01, out.s0); - DOT16X16(in, weights11, out1.s0); - DOT16X16(in, weights21, out2.s0); - DOT16X16(in, weights31, out3.s0); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16 + 16)); - DOT16X16(in, weights01, out.s1); - DOT16X16(in, weights11, out1.s1); - DOT16X16(in, weights21, out2.s1); - DOT16X16(in, weights31, out3.s1); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16 + 32)); - DOT16X16(in, weights01, out.s2); - DOT16X16(in, weights11, out1.s2); - DOT16X16(in, weights21, out2.s2); - DOT16X16(in, weights31, out3.s2); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16 + 48)); - DOT16X16(in, weights01, out.s3); - DOT16X16(in, weights11, out1.s3); - DOT16X16(in, weights21, out2.s3); - DOT16X16(in, weights31, out3.s3); - #else - int k32 = k << 5; - COMPUTE_FLOAT *weights00_ptr = (COMPUTE_FLOAT *)&weights00; - COMPUTE_FLOAT *weights10_ptr = (COMPUTE_FLOAT *)&weights10; - COMPUTE_FLOAT *weights20_ptr = (COMPUTE_FLOAT *)&weights20; - COMPUTE_FLOAT *weights30_ptr = (COMPUTE_FLOAT *)&weights30; - COMPUTE_FLOAT *weights01_ptr = (COMPUTE_FLOAT *)&weights01; - COMPUTE_FLOAT *weights11_ptr = (COMPUTE_FLOAT *)&weights11; - COMPUTE_FLOAT *weights21_ptr = (COMPUTE_FLOAT *)&weights21; - COMPUTE_FLOAT *weights31_ptr = (COMPUTE_FLOAT *)&weights31; - #pragma unroll - for (int i = 0; i < 16; ++i){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i) * 4)); - out = mad(in, weights00_ptr[i], out); - out1 = mad(in, weights10_ptr[i], out1); - out2 = mad(in, weights20_ptr[i], out2); - out3 = mad(in, weights30_ptr[i], out3); - } - #pragma unroll - for (int i = 0; i < 16; ++i){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i + 16) * 4)); - out = mad(in, weights01_ptr[i], out); - out1 = mad(in, weights11_ptr[i], out1); - out2 = mad(in, weights21_ptr[i], out2); - out3 = mad(in, weights31_ptr[i], out3); + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + COMPUTE_FLOAT8 wei; + #ifdef USE_IMAGE + uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(k, y))); + #else + uchar16 charWeightsInt40 = vload16(k, weight + weight_offset); + #endif + COMPUTE_FLOAT4 in0 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4)); + #if INPUT_BATCH_LEAVES_NUM >= 2 + COMPUTE_FLOAT4 in1 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4 + 4)); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + COMPUTE_FLOAT4 in2 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4 + 8)); + #endif + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s0123, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in0.s0, wei, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s0, wei, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s0, wei, out2); + #endif + } + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s4567, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in0.s1, wei, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s1, wei, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s1, wei, out2); + #endif + } + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s89ab, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in0.s2, wei, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s2, wei, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s2, wei, out2); + #endif + } + { + UCHAR4_TO_FLOAT8(charWeightsInt40.scdef, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in0.s3, wei, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s3, wei, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s3, wei, out2); + #endif + } } - #endif - #else - COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; - #ifdef USE_IMAGE - weights0 = readWeight(weight, out_c_idx, k, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight, out_c_idx + 1, k, ScaleOffset.s2, ScaleOffset.s3); - weights2 = readWeight(weight, out_c_idx + 2, k, ScaleOffset.s4, ScaleOffset.s5); - weights3 = readWeight(weight, out_c_idx + 3, k, ScaleOffset.s6, ScaleOffset.s7); - #else - weights0 = readWeight(weight + weight_offset + k * weight_oc_offset, 0, 0, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight + weight_offset + k * weight_oc_offset + WEIGHT_STRIDE, 0, 0, ScaleOffset.s2, ScaleOffset.s3); - weights2 = readWeight(weight + weight_offset + k * weight_oc_offset + 2 * WEIGHT_STRIDE, 0, 0, ScaleOffset.s4, ScaleOffset.s5); - weights3 = readWeight(weight + weight_offset + k * weight_oc_offset + 3 * WEIGHT_STRIDE, 0, 0, ScaleOffset.s6, ScaleOffset.s7); - #endif - #ifdef FORMAT_CNHW - COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16)); - DOT16X16(in, weights0, out.s0); - DOT16X16(in, weights1, out1.s0); - DOT16X16(in, weights2, out2.s0); - DOT16X16(in, weights3, out3.s0); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16 + 16)); - DOT16X16(in, weights0, out.s1); - DOT16X16(in, weights1, out1.s1); - DOT16X16(in, weights2, out2.s1); - DOT16X16(in, weights3, out3.s1); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16 + 32)); - DOT16X16(in, weights0, out.s2); - DOT16X16(in, weights1, out1.s2); - DOT16X16(in, weights2, out2.s2); - DOT16X16(in, weights3, out3.s2); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16 + 48)); - DOT16X16(in, weights0, out.s3); - DOT16X16(in, weights1, out1.s3); - DOT16X16(in, weights2, out2.s3); - DOT16X16(in, weights3, out3.s3); - #else - int k16 = k << 4; - COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; - COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; - COMPUTE_FLOAT *weights2_ptr = (COMPUTE_FLOAT *)&weights2; - COMPUTE_FLOAT *weights3_ptr = (COMPUTE_FLOAT *)&weights3; - #pragma unroll - for (int i = 0; i < 16; ++i){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); - out = mad(in, weights0_ptr[i], out); - out1 = mad(in, weights1_ptr[i], out1); - out2 = mad(in, weights2_ptr[i], out2); - out3 = mad(in, weights3_ptr[i], out3); + #if INPUT_CHANNEL_LEAVES_NUM != 0 + { + int k = i * loop + loop_end; + COMPUTE_FLOAT8 wei; + COMPUTE_FLOAT4 in0 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4)); + #if INPUT_BATCH_LEAVES_NUM >= 2 + COMPUTE_FLOAT4 in1 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4 + 4)); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + COMPUTE_FLOAT4 in2 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4 + 8)); + #endif + #ifdef USE_IMAGE + uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(k, y))); + #else + uchar16 charWeightsInt40 = vload16(k, weight + weight_offset); + #endif + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s0123, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in0.s0, wei, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s0, wei, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s0, wei, out2); + #endif + } + #if INPUT_CHANNEL_LEAVES_NUM >= 2 + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s4567, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in0.s1, wei, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s1, wei, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s1, wei, out2); + #endif + } + #endif + #if INPUT_CHANNEL_LEAVES_NUM >= 3 + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s89ab, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in0.s2, wei, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s2, wei, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s2, wei, out2); + #endif + } + #endif } #endif - #endif } - } -#ifdef RELU - out = fmax(out, (COMPUTE_FLOAT4)0); - out1 = fmax(out1, (COMPUTE_FLOAT4)0); - out2 = fmax(out2, (COMPUTE_FLOAT4)0); - out3 = fmax(out3, (COMPUTE_FLOAT4)0); -#endif - -#ifdef RELU6 - out = clamp(out, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); - out1 = clamp(out1, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); - out2 = clamp(out2, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); - out3 = clamp(out3, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); -#endif - - vstore4(CONVERT_FLOAT4(out), 0, output+out_offset); - vstore4(CONVERT_FLOAT4(out1), 0, output+out_offset + 4); - vstore4(CONVERT_FLOAT4(out2), 0, output+out_offset + 8); - vstore4(CONVERT_FLOAT4(out3), 0, output+out_offset + 12); -} - -__kernel void gemm_b4_c2_buf(GLOBAL_SIZE_DIM2 - __global const FLOAT* input, -#ifdef USE_IMAGE - __read_only image2d_t weight, -#else -#if (defined USE_LOW_BIT_WEIGHT_INT8) - __global const char *weight, -#elif (defined USE_LOW_BIT_WEIGHT_INT4) - __global const uchar *weight, -#endif -#endif - __global const float *dequantScaleOffset, - __global const FLOAT *bias, - __global FLOAT* output, - __private const int bhw4, - __private const int dstChannelAlign, - __private const int srcChannelAlign, - __private const int blockNum, - __private const int blockDim) { - const int x = get_global_id(0); //c - const int y = get_global_id(1); //b - - UNIFORM_BOUNDRY_CHECK(x, y); - - const int out_c_idx = x << 1; - const int out_b_idx = y << 2; - - COMPUTE_FLOAT2 bias0 = CONVERT_COMPUTE_FLOAT2(vload2(0, bias + out_c_idx)); - COMPUTE_FLOAT4 out = (COMPUTE_FLOAT4)bias0.s0; - COMPUTE_FLOAT4 out1 = (COMPUTE_FLOAT4)bias0.s1; - -#ifdef FORMAT_CNHW - int input_offset = out_b_idx * 16; -#else - int input_offset = out_b_idx * srcChannelAlign; -#endif - int out_offset = out_b_idx * dstChannelAlign + out_c_idx * 4; - -#ifndef USE_IMAGE - int weight_offset = out_c_idx * WEIGHT_STRIDE; - int weight_oc_offset = dstChannelAlign * WEIGHT_STRIDE; + } else { #endif - - const int loop = (blockDim + CHANNEL_PACK - 1) / CHANNEL_PACK; - for (int i = 0; i < blockNum; i++){ - int kindex = i * dstChannelAlign * 2; - COMPUTE_FLOAT4 ScaleOffset = CONVERT_COMPUTE_FLOAT4(vload4(0, dequantScaleOffset + kindex + out_c_idx * 2)); - for (int j = 0; j < loop; j++) { + COMPUTE_FLOAT8 scale, offset; + { + COMPUTE_FLOAT16 scaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + (out_c_idx << 3) + i * dstChannelAlign * 2)); + scale = scaleOffset.s02468ace; + offset = scaleOffset.s13579bdf; + } + for (int j = 0; j < loop_end; j++) { int k = i * loop + j; - #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) - COMPUTE_FLOAT16 weights00, weights01, weights10, weights11; + COMPUTE_FLOAT8 wei; + COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4)); + #ifdef USE_IMAGE + uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(k, y))); + #else + uchar16 charWeightsInt40 = vload16(k, weight + weight_offset); + #endif { - uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); - uchar16 charWeightsInt41 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 1, k))); - char16 charWeights0, charWeights1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights00 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; - weights01 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); - weights10 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; - weights11 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + UCHAR4_TO_FLOAT8(charWeightsInt40.s0123, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s0, wei, out0); + out1 = mad((COMPUTE_FLOAT8)in.s4, wei, out1); + out2 = mad((COMPUTE_FLOAT8)in.s8, wei, out2); + out3 = mad((COMPUTE_FLOAT8)in.sc, wei, out3); } - #ifdef FORMAT_CNHW - int k2 = k << 1; - COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16)); - DOT16X16(in, weights00, out.s0); - DOT16X16(in, weights10, out1.s0); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16 + 16)); - DOT16X16(in, weights00, out.s1); - DOT16X16(in, weights10, out1.s1); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16 + 32)); - DOT16X16(in, weights00, out.s2); - DOT16X16(in, weights10, out1.s2); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16 + 48)); - DOT16X16(in, weights00, out.s3); - DOT16X16(in, weights10, out1.s3); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16)); - DOT16X16(in, weights01, out.s0); - DOT16X16(in, weights11, out1.s0); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16 + 16)); - DOT16X16(in, weights01, out.s1); - DOT16X16(in, weights11, out1.s1); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16 + 32)); - DOT16X16(in, weights01, out.s2); - DOT16X16(in, weights11, out1.s2); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16 + 48)); - DOT16X16(in, weights01, out.s3); - DOT16X16(in, weights11, out1.s3); - #else - int k32 = k << 5; - COMPUTE_FLOAT *weights00_ptr = (COMPUTE_FLOAT *)&weights00; - COMPUTE_FLOAT *weights10_ptr = (COMPUTE_FLOAT *)&weights10; - COMPUTE_FLOAT *weights01_ptr = (COMPUTE_FLOAT *)&weights01; - COMPUTE_FLOAT *weights11_ptr = (COMPUTE_FLOAT *)&weights11; - #pragma unroll - for (int i = 0; i < 16; ++i){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i) * 4)); - out = mad(in, weights00_ptr[i], out); - out1 = mad(in, weights10_ptr[i], out1); + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s4567, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s1, wei, out0); + out1 = mad((COMPUTE_FLOAT8)in.s5, wei, out1); + out2 = mad((COMPUTE_FLOAT8)in.s9, wei, out2); + out3 = mad((COMPUTE_FLOAT8)in.sd, wei, out3); } - #pragma unroll - for (int i = 0; i < 16; ++i){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i + 16) * 4)); - out = mad(in, weights01_ptr[i], out); - out1 = mad(in, weights11_ptr[i], out1); + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s89ab, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s2, wei, out0); + out1 = mad((COMPUTE_FLOAT8)in.s6, wei, out1); + out2 = mad((COMPUTE_FLOAT8)in.sa, wei, out2); + out3 = mad((COMPUTE_FLOAT8)in.se, wei, out3); } - #endif - #else - COMPUTE_FLOAT16 weights0, weights1; + { + UCHAR4_TO_FLOAT8(charWeightsInt40.scdef, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s3, wei, out0); + out1 = mad((COMPUTE_FLOAT8)in.s7, wei, out1); + out2 = mad((COMPUTE_FLOAT8)in.sb, wei, out2); + out3 = mad((COMPUTE_FLOAT8)in.sf, wei, out3); + } + } + #if INPUT_CHANNEL_LEAVES_NUM != 0 + { + int k = i * loop + loop_end; + COMPUTE_FLOAT8 wei; + COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4)); #ifdef USE_IMAGE - weights0 = readWeight(weight, out_c_idx, k, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight, out_c_idx + 1, k, ScaleOffset.s2, ScaleOffset.s3); + uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(k, y))); #else - weights0 = readWeight(weight + weight_offset + k * weight_oc_offset, 0, 0, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight + weight_offset + k * weight_oc_offset + WEIGHT_STRIDE, 0, 0, ScaleOffset.s2, ScaleOffset.s3); + uchar16 charWeightsInt40 = vload16(k, weight + weight_offset); #endif - #ifdef FORMAT_CNHW - COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16)); - DOT16X16(in, weights0, out.s0); - DOT16X16(in, weights1, out1.s0); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16 + 16)); - DOT16X16(in, weights0, out.s1); - DOT16X16(in, weights1, out1.s1); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16 + 32)); - DOT16X16(in, weights0, out.s2); - DOT16X16(in, weights1, out1.s2); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16 + 48)); - DOT16X16(in, weights0, out.s3); - DOT16X16(in, weights1, out1.s3); - #else - int k16 = k << 4; - COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; - COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; - #pragma unroll - for (int i = 0; i < 16; ++i){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); - out = mad(in, weights0_ptr[i], out); - out1 = mad(in, weights1_ptr[i], out1); + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s0123, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s0, wei, out0); + out1 = mad((COMPUTE_FLOAT8)in.s4, wei, out1); + out2 = mad((COMPUTE_FLOAT8)in.s8, wei, out2); + out3 = mad((COMPUTE_FLOAT8)in.sc, wei, out3); + } + #if INPUT_CHANNEL_LEAVES_NUM >= 2 + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s4567, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s1, wei, out0); + out1 = mad((COMPUTE_FLOAT8)in.s5, wei, out1); + out2 = mad((COMPUTE_FLOAT8)in.s9, wei, out2); + out3 = mad((COMPUTE_FLOAT8)in.sd, wei, out3); } #endif + #if INPUT_CHANNEL_LEAVES_NUM >= 3 + { + UCHAR4_TO_FLOAT8(charWeightsInt40.s89ab, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s2, wei, out0); + out1 = mad((COMPUTE_FLOAT8)in.s6, wei, out1); + out2 = mad((COMPUTE_FLOAT8)in.sa, wei, out2); + out3 = mad((COMPUTE_FLOAT8)in.se, wei, out3); + } #endif } + #endif } +#if INPUT_BATCH_LEAVES_NUM != 0 + } +#endif #ifdef RELU - out = fmax(out, (COMPUTE_FLOAT4)0); - out1 = fmax(out1, (COMPUTE_FLOAT4)0); + out0 = fmax(out0, (COMPUTE_FLOAT8)0); + out1 = fmax(out1, (COMPUTE_FLOAT8)0); + out2 = fmax(out2, (COMPUTE_FLOAT8)0); + out3 = fmax(out3, (COMPUTE_FLOAT8)0); #endif #ifdef RELU6 - out = clamp(out, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); - out1 = clamp(out1, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); + out0 = clamp(out0, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); + out1 = clamp(out1, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); + out2 = clamp(out2, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); + out3 = clamp(out3, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); #endif - - vstore4(CONVERT_FLOAT4(out), 0, output+out_offset); - vstore4(CONVERT_FLOAT4(out1), 0, output+out_offset+4); + vstore4(CONVERT_FLOAT4(out0.s0123), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out0.s4567), 0, output+out_offset+bhw4); + if(out_b_idx + 1 >= bhw) return; + out_offset += 4; + vstore4(CONVERT_FLOAT4(out1.s0123), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out1.s4567), 0, output+out_offset+bhw4); + if(out_b_idx + 2 >= bhw) return; + out_offset += 4; + vstore4(CONVERT_FLOAT4(out2.s0123), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out2.s4567), 0, output+out_offset+bhw4); + if(out_b_idx + 3 >= bhw) return; + out_offset += 4; + vstore4(CONVERT_FLOAT4(out3.s0123), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out3.s4567), 0, output+out_offset+bhw4); } -__kernel void gemm_b4_c1_buf(GLOBAL_SIZE_DIM2 + +__kernel void gemm_b4_c8_int8_buf(GLOBAL_SIZE_DIM2 __global const FLOAT* input, #ifdef USE_IMAGE __read_only image2d_t weight, #else -#if (defined USE_LOW_BIT_WEIGHT_INT8) __global const char *weight, -#elif (defined USE_LOW_BIT_WEIGHT_INT4) - __global const uchar *weight, -#endif #endif __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT* output, - __private const int bhw4, + __private const int bhw, __private const int dstChannelAlign, __private const int srcChannelAlign, __private const int blockNum, __private const int blockDim) { - const int x = get_global_id(0); //c - const int y = get_global_id(1); //b + const int x = get_global_id(0); //b/4 + const int y = get_global_id(1); //c/8 UNIFORM_BOUNDRY_CHECK(x, y); + + const int out_b_idx = x << 2; + const int out_c_idx = y << 1; - const int out_c_idx = x; - const int out_b_idx = y << 2; - - COMPUTE_FLOAT bias0 = bias[out_c_idx]; - COMPUTE_FLOAT4 out = (COMPUTE_FLOAT4)bias0; + COMPUTE_FLOAT8 out0 = CONVERT_FLOAT8(vload8(0, bias + (out_c_idx << 2))); + COMPUTE_FLOAT8 out1 = out0; + COMPUTE_FLOAT8 out2 = out0; + COMPUTE_FLOAT8 out3 = out0; -#ifdef FORMAT_CNHW - int input_offset = out_b_idx * 16; + const int bhw4 = bhw << 2; + const int input_offset = out_b_idx * 4; + int out_offset = out_c_idx * bhw4 + out_b_idx * 4; +#ifndef USE_IMAGE + const int weight_offset = y * srcChannelAlign * 8; +#endif + const int loop = (blockDim + 4 - 1) / 4; +#if INPUT_CHANNEL_LEAVES_NUM != 0 + const int loop_end = max(loop - 1, 0); #else - int input_offset = out_b_idx * srcChannelAlign; + const int loop_end = loop; #endif - int out_offset = out_b_idx * dstChannelAlign + out_c_idx * 4; -#ifndef USE_IMAGE - int weight_offset = out_c_idx * WEIGHT_STRIDE; - int weight_oc_offset = dstChannelAlign * WEIGHT_STRIDE; +#if INPUT_BATCH_LEAVES_NUM != 0 + if(out_b_idx + 3 >= bhw){ + for (int i = 0; i < blockNum; i++){ + COMPUTE_FLOAT16 scale, offset; + { + COMPUTE_FLOAT16 scaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + (out_c_idx << 3) + i * dstChannelAlign * 2)); + scale = (COMPUTE_FLOAT16)(scaleOffset.s02468ace, scaleOffset.s02468ace); + offset = (COMPUTE_FLOAT16)(scaleOffset.s13579bdf, scaleOffset.s13579bdf); + } + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + int k2 = k << 1; + #ifdef USE_IMAGE + COMPUTE_FLOAT16 wei0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(k2, y)))) * scale + offset; + COMPUTE_FLOAT16 wei1 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(k2 + 1, y)))) * scale + offset; + #else + COMPUTE_FLOAT16 wei0 = CONVERT_COMPUTE_FLOAT16(vload16(k2, weight + weight_offset)) * scale + offset; + COMPUTE_FLOAT16 wei1 = CONVERT_COMPUTE_FLOAT16(vload16(k2 + 1, weight + weight_offset)) * scale + offset; + #endif + COMPUTE_FLOAT4 in0 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4)); + #if INPUT_BATCH_LEAVES_NUM >= 2 + COMPUTE_FLOAT4 in1 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4 + 4)); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + COMPUTE_FLOAT4 in2 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4 + 8)); + #endif + { + out0 = mad((COMPUTE_FLOAT8)in0.s0, wei0.s01234567, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s0, wei0.s01234567, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s0, wei0.s01234567, out2); + #endif + } + { + out0 = mad((COMPUTE_FLOAT8)in0.s1, wei0.s89abcdef, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s1, wei0.s89abcdef, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s1, wei0.s89abcdef, out2); + #endif + } + { + out0 = mad((COMPUTE_FLOAT8)in0.s2, wei1.s01234567, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s2, wei1.s01234567, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s2, wei1.s01234567, out2); + #endif + } + { + out0 = mad((COMPUTE_FLOAT8)in0.s3, wei1.s89abcdef, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s3, wei1.s89abcdef, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s3, wei1.s89abcdef, out2); + #endif + } + } + #if INPUT_CHANNEL_LEAVES_NUM != 0 + { + int k = i * loop + loop_end; + int k2 = k << 1; + COMPUTE_FLOAT4 in0 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4)); + #if INPUT_BATCH_LEAVES_NUM >= 2 + COMPUTE_FLOAT4 in1 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4 + 4)); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + COMPUTE_FLOAT4 in2 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k * bhw4 + 8)); + #endif + #ifdef USE_IMAGE + COMPUTE_FLOAT16 wei0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(k2, y)))) * scale + offset; + COMPUTE_FLOAT16 wei1 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(k2 + 1, y)))) * scale + offset; + #else + COMPUTE_FLOAT16 wei0 = CONVERT_COMPUTE_FLOAT16(vload16(k2, weight + weight_offset)) * scale + offset; + COMPUTE_FLOAT16 wei1 = CONVERT_COMPUTE_FLOAT16(vload16(k2 + 1, weight + weight_offset)) * scale + offset; + #endif + { + out0 = mad((COMPUTE_FLOAT8)in0.s0, wei0.s01234567, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s0, wei0.s01234567, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s0, wei0.s01234567, out2); + #endif + } + #if INPUT_CHANNEL_LEAVES_NUM >= 2 + { + out0 = mad((COMPUTE_FLOAT8)in0.s1, wei0.s89abcdef, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s1, wei0.s89abcdef, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s1, wei0.s89abcdef, out2); + #endif + } + #endif + #if INPUT_CHANNEL_LEAVES_NUM >= 3 + { + out0 = mad((COMPUTE_FLOAT8)in0.s2, wei1.s01234567, out0); + #if INPUT_BATCH_LEAVES_NUM >= 2 + out1 = mad((COMPUTE_FLOAT8)in1.s2, wei1.s01234567, out1); + #endif + #if INPUT_BATCH_LEAVES_NUM >= 3 + out2 = mad((COMPUTE_FLOAT8)in2.s2, wei1.s01234567, out2); + #endif + } + #endif + } + #endif + } + } else { #endif - - const int loop = (blockDim + CHANNEL_PACK - 1) / CHANNEL_PACK; - for (int i = 0; i < blockNum; i++){ - int kindex = i * dstChannelAlign * 2; - COMPUTE_FLOAT2 ScaleOffset = CONVERT_COMPUTE_FLOAT2(vload2(out_c_idx, dequantScaleOffset + kindex)); - for (int j = 0; j < loop; j++) { + COMPUTE_FLOAT16 scale, offset; + { + COMPUTE_FLOAT16 scaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + (out_c_idx << 3) + i * dstChannelAlign * 2)); + scale = (COMPUTE_FLOAT16)(scaleOffset.s02468ace, scaleOffset.s02468ace); + offset = (COMPUTE_FLOAT16)(scaleOffset.s13579bdf, scaleOffset.s13579bdf); + } + for (int j = 0; j < loop_end; j++) { int k = i * loop + j; - #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) - COMPUTE_FLOAT16 weights00, weights01, weights10, weights11; - { - uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); - char16 charWeights0, charWeights1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights00 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; - weights01 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; - } - #ifdef FORMAT_CNHW int k2 = k << 1; - COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16)); - DOT16X16(in, weights00, out.s0); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16 + 16)); - DOT16X16(in, weights00, out.s1); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16 + 32)); - DOT16X16(in, weights00, out.s2); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k2 * bhw4 * 16 + 48)); - DOT16X16(in, weights00, out.s3); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16)); - DOT16X16(in, weights01, out.s0); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16 + 16)); - DOT16X16(in, weights01, out.s1); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16 + 32)); - DOT16X16(in, weights01, out.s2); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + (k2 + 1) * bhw4 * 16 + 48)); - DOT16X16(in, weights01, out.s3); + COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4)); + #ifdef USE_IMAGE + COMPUTE_FLOAT16 wei0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(k2, y)))) * scale + offset; + COMPUTE_FLOAT16 wei1 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(k2 + 1, y)))) * scale + offset; #else - int k32 = k << 5; - COMPUTE_FLOAT *weights00_ptr = (COMPUTE_FLOAT *)&weights00; - COMPUTE_FLOAT *weights01_ptr = (COMPUTE_FLOAT *)&weights01; - #pragma unroll - for (int i = 0; i < 16; ++i){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i) * 4)); - out = mad(in, weights00_ptr[i], out); + COMPUTE_FLOAT16 wei0 = CONVERT_COMPUTE_FLOAT16(vload16(k2, weight + weight_offset)) * scale + offset; + COMPUTE_FLOAT16 wei1 = CONVERT_COMPUTE_FLOAT16(vload16(k2 + 1, weight + weight_offset)) * scale + offset; + #endif + { + out0 = mad((COMPUTE_FLOAT8)in.s0, wei0.s01234567, out0); + out1 = mad((COMPUTE_FLOAT8)in.s4, wei0.s01234567, out1); + out2 = mad((COMPUTE_FLOAT8)in.s8, wei0.s01234567, out2); + out3 = mad((COMPUTE_FLOAT8)in.sc, wei0.s01234567, out3); } - #pragma unroll - for (int i = 0; i < 16; ++i){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i + 16) * 4)); - out = mad(in, weights01_ptr[i], out); + { + out0 = mad((COMPUTE_FLOAT8)in.s1, wei0.s89abcdef, out0); + out1 = mad((COMPUTE_FLOAT8)in.s5, wei0.s89abcdef, out1); + out2 = mad((COMPUTE_FLOAT8)in.s9, wei0.s89abcdef, out2); + out3 = mad((COMPUTE_FLOAT8)in.sd, wei0.s89abcdef, out3); } - #endif - #else - COMPUTE_FLOAT16 weights; + { + out0 = mad((COMPUTE_FLOAT8)in.s2, wei1.s01234567, out0); + out1 = mad((COMPUTE_FLOAT8)in.s6, wei1.s01234567, out1); + out2 = mad((COMPUTE_FLOAT8)in.sa, wei1.s01234567, out2); + out3 = mad((COMPUTE_FLOAT8)in.se, wei1.s01234567, out3); + } + { + out0 = mad((COMPUTE_FLOAT8)in.s3, wei1.s89abcdef, out0); + out1 = mad((COMPUTE_FLOAT8)in.s7, wei1.s89abcdef, out1); + out2 = mad((COMPUTE_FLOAT8)in.sb, wei1.s89abcdef, out2); + out3 = mad((COMPUTE_FLOAT8)in.sf, wei1.s89abcdef, out3); + } + } + #if INPUT_CHANNEL_LEAVES_NUM != 0 + { + int k = i * loop + loop_end; + int k2 = k << 1; + COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4)); #ifdef USE_IMAGE - weights = readWeight(weight, out_c_idx, k, ScaleOffset.s0, ScaleOffset.s1); + COMPUTE_FLOAT16 wei0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(k2, y)))) * scale + offset; + COMPUTE_FLOAT16 wei1 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(k2 + 1, y)))) * scale + offset; #else - weights = readWeight(weight + weight_offset + k * weight_oc_offset, 0, 0, ScaleOffset.s0, ScaleOffset.s1); + COMPUTE_FLOAT16 wei0 = CONVERT_COMPUTE_FLOAT16(vload16(k2, weight + weight_offset)) * scale + offset; + COMPUTE_FLOAT16 wei1 = CONVERT_COMPUTE_FLOAT16(vload16(k2 + 1, weight + weight_offset)) * scale + offset; #endif - #ifdef FORMAT_CNHW - COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16)); - DOT16X16(in, weights, out.s0); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16 + 16)); - DOT16X16(in, weights, out.s1); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16 + 32)); - DOT16X16(in, weights, out.s2); - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * bhw4 * 16 + 48)); - DOT16X16(in, weights, out.s3); - #else - int k16 = k << 4; - COMPUTE_FLOAT *weights_ptr = (COMPUTE_FLOAT *)&weights; - #pragma unroll - for (int i = 0; i < 16; ++i){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); - out = mad(in, weights_ptr[i], out); + { + out0 = mad((COMPUTE_FLOAT8)in.s0, wei0.s01234567, out0); + out1 = mad((COMPUTE_FLOAT8)in.s4, wei0.s01234567, out1); + out2 = mad((COMPUTE_FLOAT8)in.s8, wei0.s01234567, out2); + out3 = mad((COMPUTE_FLOAT8)in.sc, wei0.s01234567, out3); + } + #if INPUT_CHANNEL_LEAVES_NUM >= 2 + { + out0 = mad((COMPUTE_FLOAT8)in.s1, wei0.s89abcdef, out0); + out1 = mad((COMPUTE_FLOAT8)in.s5, wei0.s89abcdef, out1); + out2 = mad((COMPUTE_FLOAT8)in.s9, wei0.s89abcdef, out2); + out3 = mad((COMPUTE_FLOAT8)in.sd, wei0.s89abcdef, out3); } #endif + #if INPUT_CHANNEL_LEAVES_NUM >= 3 + { + out0 = mad((COMPUTE_FLOAT8)in.s2, wei1.s01234567, out0); + out1 = mad((COMPUTE_FLOAT8)in.s6, wei1.s01234567, out1); + out2 = mad((COMPUTE_FLOAT8)in.sa, wei1.s01234567, out2); + out3 = mad((COMPUTE_FLOAT8)in.se, wei1.s01234567, out3); + } #endif } + #endif } +#if INPUT_BATCH_LEAVES_NUM != 0 + } +#endif #ifdef RELU - out = fmax(out, (COMPUTE_FLOAT4)0); + out0 = fmax(out0, (COMPUTE_FLOAT8)0); + out1 = fmax(out1, (COMPUTE_FLOAT8)0); + out2 = fmax(out2, (COMPUTE_FLOAT8)0); + out3 = fmax(out3, (COMPUTE_FLOAT8)0); #endif #ifdef RELU6 - out = clamp(out, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); + out0 = clamp(out0, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); + out1 = clamp(out1, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); + out2 = clamp(out2, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); + out3 = clamp(out3, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); #endif - vstore4(CONVERT_FLOAT4(out), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out0.s0123), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out0.s4567), 0, output+out_offset+bhw4); + if(out_b_idx + 1 >= bhw) return; + out_offset += 4; + vstore4(CONVERT_FLOAT4(out1.s0123), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out1.s4567), 0, output+out_offset+bhw4); + if(out_b_idx + 2 >= bhw) return; + out_offset += 4; + vstore4(CONVERT_FLOAT4(out2.s0123), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out2.s4567), 0, output+out_offset+bhw4); + if(out_b_idx + 3 >= bhw) return; + out_offset += 4; + vstore4(CONVERT_FLOAT4(out3.s0123), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out3.s4567), 0, output+out_offset+bhw4); } diff --git a/source/backend/opencl/execution/cl/gemv_conv1x1_buf.cl b/source/backend/opencl/execution/cl/gemv_conv1x1_buf.cl index df362ce09..a2edaa419 100644 --- a/source/backend/opencl/execution/cl/gemv_conv1x1_buf.cl +++ b/source/backend/opencl/execution/cl/gemv_conv1x1_buf.cl @@ -2,87 +2,149 @@ #pragma OPENCL EXTENSION cl_khr_fp16 : enable #endif -#define GLOBAL_SIZE_DIM2 \ +__constant sampler_t SAMPLER = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST; +#define GLOBAL_SIZE_DIM_2 \ __private int global_size_dim0, __private int global_size_dim1, -#define UNIFORM_BOUNDRY_CHECK(index0, index1) \ +#define UNIFORM_BOUNDRY_CHECK_2(index0, index1) \ if(index0 >= global_size_dim0 || index1 >= global_size_dim1) { \ return; \ } -#define UCHAR16_TO_2CHAR16(a, b, c) \ - a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; \ - a.s8 = (c.s4 >> 4) - 8; a.s9 = (c.s4 & 15) - 8; a.sa = (c.s5 >> 4) - 8; a.sb = (c.s5 & 15) - 8; a.sc = (c.s6 >> 4) - 8; a.sd = (c.s6 & 15) - 8; a.se = (c.s7 >> 4) - 8; a.sf = (c.s7 & 15) - 8; \ - b.s0 = (c.s8 >> 4) - 8; b.s1 = (c.s8 & 15) - 8; b.s2 = (c.s9 >> 4) - 8; b.s3 = (c.s9 & 15) - 8; b.s4 = (c.sa >> 4) - 8; b.s5 = (c.sa & 15) - 8; b.s6 = (c.sb >> 4) - 8; b.s7 = (c.sb & 15) - 8; \ - b.s8 = (c.sc >> 4) - 8; b.s9 = (c.sc & 15) - 8; b.sa = (c.sd >> 4) - 8; b.sb = (c.sd & 15) - 8; b.sc = (c.se >> 4) - 8; b.sd = (c.se & 15) - 8; b.se = (c.sf >> 4) - 8; b.sf = (c.sf & 15) - 8; - -#define UCHAR8_TO_CHAR16(a, c) \ - a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; \ - a.s8 = (c.s4 >> 4) - 8; a.s9 = (c.s4 & 15) - 8; a.sa = (c.s5 >> 4) - 8; a.sb = (c.s5 & 15) - 8; a.sc = (c.s6 >> 4) - 8; a.sd = (c.s6 & 15) - 8; a.se = (c.s7 >> 4) - 8; a.sf = (c.s7 & 15) - 8; +#define UCHAR4_TO_CHAR8(b, scale, offset) \ + wei.s0 = (COMPUTE_FLOAT)((b.s0 >> 4) - 8); \ + wei.s1 = (COMPUTE_FLOAT)((b.s0 & 15) - 8); \ + wei.s2 = (COMPUTE_FLOAT)((b.s1 >> 4) - 8); \ + wei.s3 = (COMPUTE_FLOAT)((b.s1 & 15) - 8); \ + wei.s4 = (COMPUTE_FLOAT)((b.s2 >> 4) - 8); \ + wei.s5 = (COMPUTE_FLOAT)((b.s2 & 15) - 8); \ + wei.s6 = (COMPUTE_FLOAT)((b.s3 >> 4) - 8); \ + wei.s7 = (COMPUTE_FLOAT)((b.s3 & 15) - 8); \ + wei = wei * scale + offset; -#define DOT16X16(a, b, c) \ - c += dot(a.s0123, b.s0123); \ - c += dot(a.s4567, b.s4567); \ - c += dot(a.s89ab, b.s89ab); \ - c += dot(a.scdef, b.scdef); -#ifdef INPUT_CHANNEL_LEAVE - #define PADZEROS(k, channel, data) {\ - COMPUTE_FLOAT* ptr = (COMPUTE_FLOAT*)&data; \ - int remain = k + 15 - channel; \ - for(int r = remain; r >= 0; r--){ \ - ptr[15 - r] = 0; \ - } \ - } +#if WGS >= 8 +__kernel void gemv_conv_c8_int4_buf(GLOBAL_SIZE_DIM_2 + __global const FLOAT* input, +#ifdef USE_IMAGE + __read_only image2d_t weight, #else - #define PADZEROS(k, channel, data) + __global const uchar *weight, #endif - -#if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) -#define CHANNEL_PACK 32 + __global const float *dequantScaleOffset, + __global const FLOAT *bias, + __global FLOAT* output, + __private const int dstChannelC4, + __private const int srcChannelC4, + __private const int srcChannel, + __private const int blockNum, + __private const int blockDim) { + const int lid = get_local_id(0); + const int oc = get_global_id(1); //oc/8 + const int oc8 = oc << 3; +#if INPUT_CHANNEL_LEAVES_NUM != 0 + const int loop = max((srcChannel + 4 - 1) / 4 - 1, 0); #else -#define CHANNEL_PACK 16 + const int loop = (srcChannel + 4 - 1) / 4; #endif - -#if (defined USE_LOW_BIT_WEIGHT_INT8) -#define WEIGHT_STRIDE 16 -#elif (defined USE_LOW_BIT_WEIGHT_INT4) -#define WEIGHT_STRIDE 8 -#endif - -__constant sampler_t SAMPLER = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST; -#ifdef USE_IMAGE -inline COMPUTE_FLOAT16 readWeight(__read_only image2d_t weight, int ix, int iy, COMPUTE_FLOAT scale, COMPUTE_FLOAT offset){ - return CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(ix, iy)))) * scale + offset; -} -#else - -#if (defined USE_LOW_BIT_WEIGHT_INT8) -inline COMPUTE_FLOAT16 readWeight(__global const char *weight, int ix, int iy, COMPUTE_FLOAT scale, COMPUTE_FLOAT offset){ - return CONVERT_COMPUTE_FLOAT16(vload16(0, weight)) * scale + offset; -} -#elif (defined USE_LOW_BIT_WEIGHT_INT4) -inline COMPUTE_FLOAT16 readWeight(__global const uchar *weight, int ix, int iy, COMPUTE_FLOAT scale, COMPUTE_FLOAT offset){ - uchar16 charWeightsInt40 = vload16(0, weight); - uchar8 charWeightsInt4 = vload8(0, weight); - char16 charWeights = 0; - UCHAR8_TO_CHAR16(charWeights, charWeightsInt4); - return CONVERT_COMPUTE_FLOAT16(charWeights) * scale + offset; -} + __local COMPUTE_FLOAT8 sum[WGS]; + COMPUTE_FLOAT8 out0 = 0; +#ifndef USE_IMAGE + const int weight_offset = oc * srcChannelC4 * 16; #endif + + for(int j = lid; j < loop; j+=WGS){ + int k4 = j << 2; + COMPUTE_FLOAT8 scale, offset; + { + COMPUTE_FLOAT16 scaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + oc8 * 2 + (k4 / blockDim) * dstChannelC4 * 8)); + scale = scaleOffset.s02468ace; + offset = scaleOffset.s13579bdf; + } + COMPUTE_FLOAT8 wei; + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + k4)); + #ifdef USE_IMAGE + uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(j, oc))); + #else + uchar16 charWeightsInt40 = vload16(j, weight + weight_offset); + #endif + { + UCHAR4_TO_CHAR8(charWeightsInt40.s0123, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s0, wei, out0); + } + { + UCHAR4_TO_CHAR8(charWeightsInt40.s4567, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s1, wei, out0); + } + { + UCHAR4_TO_CHAR8(charWeightsInt40.s89ab, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s2, wei, out0); + } + { + UCHAR4_TO_CHAR8(charWeightsInt40.scdef, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s3, wei, out0); + } + } +#if INPUT_CHANNEL_LEAVES_NUM != 0 + { + int k4 = loop << 2; + COMPUTE_FLOAT8 scale, offset; + { + COMPUTE_FLOAT16 scaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + oc8 * 2 + (k4 / blockDim) * dstChannelC4 * 8)); + scale = scaleOffset.s02468ace; + offset = scaleOffset.s13579bdf; + } + COMPUTE_FLOAT8 wei; + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + k4)); + #ifdef USE_IMAGE + uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(j, oc))); + #else + uchar16 charWeightsInt40 = vload16(j, weight + weight_offset); + #endif + { + UCHAR4_TO_CHAR8(charWeightsInt40.s0123, scale, offset); + out0 = mad((COMPUTE_FLOAT8)input[k4], wei, out0); + } + #if INPUT_CHANNEL_LEAVES_NUM >= 2 + { + UCHAR4_TO_CHAR8(charWeightsInt40.s4567, scale, offset); + out0 = mad((COMPUTE_FLOAT8)input[k4 + 1], wei, out0); + } + #endif + #if INPUT_CHANNEL_LEAVES_NUM >= 3 + { + UCHAR4_TO_CHAR8(charWeightsInt40.s89ab, scale, offset); + out0 = mad((COMPUTE_FLOAT8)input[k4 + 2], wei, out0); + } + #endif + } #endif + sum[lid] = out0; + barrier(CLK_LOCAL_MEM_FENCE); + for(int i = WGS/2; i > 0; i /= 2){ + if (lid < i) + sum[lid] = sum[lid] + sum[lid + i]; + barrier(CLK_LOCAL_MEM_FENCE); + } + if(lid == 0){ + out0 = sum[0] + CONVERT_COMPUTE_FLOAT8(vload8(0, bias + oc8)); + #ifdef RELU + out0 = fmax(out0, (COMPUTE_FLOAT8)0); + #endif + #ifdef RELU6 + out0 = clamp(out0, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); + #endif + vstore8(CONVERT_FLOAT8(out0), 0, output + oc8); + } +} -__kernel void gemv_conv_c4_buf(GLOBAL_SIZE_DIM2 +__kernel void gemv_conv_c8_int8_buf(GLOBAL_SIZE_DIM_2 __global const FLOAT* input, #ifdef USE_IMAGE __read_only image2d_t weight, #else -#if (defined USE_LOW_BIT_WEIGHT_INT8) __global const char *weight, -#elif (defined USE_LOW_BIT_WEIGHT_INT4) - __global const uchar *weight, -#endif #endif __global const float *dequantScaleOffset, __global const FLOAT *bias, @@ -90,190 +152,88 @@ __kernel void gemv_conv_c4_buf(GLOBAL_SIZE_DIM2 __private const int dstChannelC4, __private const int srcChannelC4, __private const int srcChannel, - __private const int bhw, __private const int blockNum, __private const int blockDim) { - const int x = get_global_id(0); //c/4 - const int y = get_global_id(1); //b h w - - UNIFORM_BOUNDRY_CHECK(x, y); - - COMPUTE_FLOAT4 bias0 = CONVERT_COMPUTE_FLOAT4(vload4(x, bias)); - COMPUTE_FLOAT4 out0 = bias0; - int idn = x << 2; - int idm = y; - - int input_offset0 = idm * 4; - - int out_offset = (x * bhw + idm) * 4; -#ifndef USE_IMAGE - int weight_offset = x * 4 * WEIGHT_STRIDE; - int weight_oc_offset = dstChannelC4 * 4 * WEIGHT_STRIDE; -#endif - - const int loop = (blockDim + CHANNEL_PACK - 1) / CHANNEL_PACK; -#ifdef INPUT_CHANNEL_LEAVE - const int loop_end = max(loop - 1, 0); + const int lid = get_local_id(0); + const int oc = get_global_id(1); //oc/8 + const int oc8 = oc << 3; +#if INPUT_CHANNEL_LEAVES_NUM != 0 + const int loop = max((srcChannel + 2 - 1) / 2 - 1, 0); #else - const int loop_end = loop; + const int loop = (srcChannel + 2 - 1) / 2; #endif - - for (int i = 0; i < blockNum; ++i){ - int kindex = i * dstChannelC4 * 4 * 2; - COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(x, dequantScaleOffset + kindex)); - for (int j = 0; j < loop_end; ++j) { - int k = i * loop + j; - #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) - int k32 = k << 5; - COMPUTE_FLOAT16 weights00, weights01, weights10, weights11, weights20, weights21, weights30, weights31; - { - uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn, k))); - uchar16 charWeightsInt41 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn + 1, k))); - uchar16 charWeightsInt42 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn + 2, k))); - uchar16 charWeightsInt43 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn + 3, k))); - char16 charWeights0, charWeights1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights00 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; - weights01 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); - weights10 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; - weights11 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt42); - weights20 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s4 + ScaleOffset.s5; - weights21 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s4 + ScaleOffset.s5; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt43); - weights30 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s6 + ScaleOffset.s7; - weights31 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s6 + ScaleOffset.s7; - } - { - COMPUTE_FLOAT16 in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + k32)); - COMPUTE_FLOAT16 in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + k32 + 16)); - DOT16X16(in0, weights00, out0.s0);DOT16X16(in1, weights01, out0.s0); - DOT16X16(in0, weights10, out0.s1);DOT16X16(in1, weights11, out0.s1); - DOT16X16(in0, weights20, out0.s2);DOT16X16(in1, weights21, out0.s2); - DOT16X16(in0, weights30, out0.s3);DOT16X16(in1, weights31, out0.s3); - } - #else - COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; - #ifdef USE_IMAGE - weights0 = readWeight(weight, idn, k, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight, idn + 1, k, ScaleOffset.s2, ScaleOffset.s3); - weights2 = readWeight(weight, idn + 2, k, ScaleOffset.s4, ScaleOffset.s5); - weights3 = readWeight(weight, idn + 3, k, ScaleOffset.s6, ScaleOffset.s7); - #else - weights0 = readWeight(weight + weight_offset + k * weight_oc_offset, 0, 0, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight + weight_offset + k * weight_oc_offset + WEIGHT_STRIDE, 0, 0, ScaleOffset.s2, ScaleOffset.s3); - weights2 = readWeight(weight + weight_offset + k * weight_oc_offset + 2 * WEIGHT_STRIDE, 0, 0, ScaleOffset.s4, ScaleOffset.s5); - weights3 = readWeight(weight + weight_offset + k * weight_oc_offset + 3 * WEIGHT_STRIDE, 0, 0, ScaleOffset.s6, ScaleOffset.s7); - #endif - { - COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(k, input)); - DOT16X16(in, weights0, out0.s0); - DOT16X16(in, weights1, out0.s1); - DOT16X16(in, weights2, out0.s2); - DOT16X16(in, weights3, out0.s3); - } - #endif + __local COMPUTE_FLOAT8 sum[WGS]; +#ifndef USE_IMAGE + const int weight_offset = oc * srcChannelC4 * 32; +#endif + COMPUTE_FLOAT8 out0 = 0; + for(int j = lid; j < loop; j+=WGS){ + int k2 = j << 1; + COMPUTE_FLOAT16 scale, offset; + { + COMPUTE_FLOAT16 scaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + oc8 * 2 + (k2 / blockDim) * dstChannelC4 * 8)); + scale = (COMPUTE_FLOAT16)(scaleOffset.s02468ace, scaleOffset.s02468ace); + offset = (COMPUTE_FLOAT16)(scaleOffset.s13579bdf, scaleOffset.s13579bdf); } - #ifdef INPUT_CHANNEL_LEAVE + COMPUTE_FLOAT2 in = CONVERT_COMPUTE_FLOAT2(vload2(0, input + k2)); + #ifdef USE_IMAGE + COMPUTE_FLOAT16 wei = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(j, oc)))) * scale + offset; + #else + COMPUTE_FLOAT16 wei = CONVERT_COMPUTE_FLOAT16(vload16(j, weight + weight_offset)) * scale + offset; + #endif { - int k = i * loop + loop_end; - #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) - int k8 = k << 3; - COMPUTE_FLOAT16 weights00, weights01, weights10, weights11, weights20, weights21, weights30, weights31; - { - uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn, k))); - uchar16 charWeightsInt41 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn + 1, k))); - uchar16 charWeightsInt42 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn + 2, k))); - uchar16 charWeightsInt43 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn + 3, k))); - char16 charWeights0, charWeights1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights00 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; - weights01 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); - weights10 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; - weights11 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt42); - weights20 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s4 + ScaleOffset.s5; - weights21 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s4 + ScaleOffset.s5; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt43); - weights30 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s6 + ScaleOffset.s7; - weights31 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s6 + ScaleOffset.s7; - - PADZEROS(k, srcChannel, weights00);PADZEROS(k + 16, srcChannel, weights01); - PADZEROS(k, srcChannel, weights10);PADZEROS(k + 16, srcChannel, weights11); - PADZEROS(k, srcChannel, weights20);PADZEROS(k + 16, srcChannel, weights21); - PADZEROS(k, srcChannel, weights30);PADZEROS(k + 16, srcChannel, weights31); - } - { - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + k8 * 4)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + (k8 + 1) * 4) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + (k8 + 2) * 4) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + (k8 + 3) * 4) : (FLOAT4)0); - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + (k8 + 4) * 4) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + (k8 + 5) * 4) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + (k8 + 6) * 4) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + (k8 + 7) * 4) : (FLOAT4)0); - DOT16X16(in0, weights00, out0.s0);DOT16X16(in1, weights01, out0.s0); - DOT16X16(in0, weights10, out0.s1);DOT16X16(in1, weights11, out0.s1); - DOT16X16(in0, weights20, out0.s2);DOT16X16(in1, weights21, out0.s2); - DOT16X16(in0, weights30, out0.s3);DOT16X16(in1, weights31, out0.s3); - } - #else - int k4 = k << 2; - COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; - #ifdef USE_IMAGE - weights0 = readWeight(weight, idn, k, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight, idn + 1, k, ScaleOffset.s2, ScaleOffset.s3); - weights2 = readWeight(weight, idn + 2, k, ScaleOffset.s4, ScaleOffset.s5); - weights3 = readWeight(weight, idn + 3, k, ScaleOffset.s6, ScaleOffset.s7); - #else - weights0 = readWeight(weight + weight_offset + k * weight_oc_offset, 0, 0, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight + weight_offset + k * weight_oc_offset + WEIGHT_STRIDE, 0, 0, ScaleOffset.s2, ScaleOffset.s3); - weights2 = readWeight(weight + weight_offset + k * weight_oc_offset + 2 * WEIGHT_STRIDE, 0, 0, ScaleOffset.s4, ScaleOffset.s5); - weights3 = readWeight(weight + weight_offset + k * weight_oc_offset + 3 * WEIGHT_STRIDE, 0, 0, ScaleOffset.s6, ScaleOffset.s7); - #endif - PADZEROS(k, srcChannel, weights0); - PADZEROS(k, srcChannel, weights1); - PADZEROS(k, srcChannel, weights2); - PADZEROS(k, srcChannel, weights3); - { - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + k4 * 4)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + (k4 + 1) * 4) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + (k4 + 2) * 4) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + (k4 + 3) * 4) : (FLOAT4)0); - DOT16X16(in, weights0, out0.s0); - DOT16X16(in, weights1, out0.s1); - DOT16X16(in, weights2, out0.s2); - DOT16X16(in, weights3, out0.s3); - } - #endif + out0 = mad((COMPUTE_FLOAT8)in.s0, wei.s01234567, out0); + } + { + out0 = mad((COMPUTE_FLOAT8)in.s1, wei.s89abcdef, out0); + } + } +#if INPUT_CHANNEL_LEAVES_NUM != 0 + { + int k2 = loop << 1; + COMPUTE_FLOAT8 scale, offset; + COMPUTE_FLOAT16 scale, offset; + { + COMPUTE_FLOAT16 scaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + oc8 * 2 + (k2 / blockDim) * dstChannelC4 * 8)); + scale = (COMPUTE_FLOAT16)(scaleOffset.s02468ace, scaleOffset.s02468ace); + offset = (COMPUTE_FLOAT16)(scaleOffset.s13579bdf, scaleOffset.s13579bdf); } + #ifdef USE_IMAGE + COMPUTE_FLOAT16 wei = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(j, oc)))) * scale + offset; + #else + COMPUTE_FLOAT16 wei = CONVERT_COMPUTE_FLOAT16(vload16(j, weight + weight_offset)) * scale + offset; #endif + { + out0 = mad((COMPUTE_FLOAT8)in[k2], wei.s01234567, out0); + } } -#ifdef RELU - out0 = fmax(out0, (COMPUTE_FLOAT4)0); -#endif - -#ifdef RELU6 - out0 = clamp(out0, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); #endif + sum[lid] = out0; + barrier(CLK_LOCAL_MEM_FENCE); + for(int i = WGS/2; i > 0; i /= 2){ + if (lid < i) + sum[lid] = sum[lid] + sum[lid + i]; + barrier(CLK_LOCAL_MEM_FENCE); + } + if(lid == 0){ + out0 = sum[0] + CONVERT_COMPUTE_FLOAT8(vload8(0, bias + oc8)); + #ifdef RELU + out0 = fmax(out0, (COMPUTE_FLOAT8)0); + #endif - vstore4(CONVERT_FLOAT4(out0), 0, output+out_offset); + #ifdef RELU6 + out0 = clamp(out0, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); + #endif + vstore8(CONVERT_FLOAT8(out0), 0, output + oc8); + } } - -__kernel void gemv_conv_c2_buf(GLOBAL_SIZE_DIM2 +#else +__kernel void gemv_conv_c8_int4_buf(GLOBAL_SIZE_DIM_2 __global const FLOAT* input, #ifdef USE_IMAGE __read_only image2d_t weight, #else -#if (defined USE_LOW_BIT_WEIGHT_INT8) - __global const char *weight, -#elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *weight, -#endif #endif __global const float *dequantScaleOffset, __global const FLOAT *bias, @@ -281,153 +241,102 @@ __kernel void gemv_conv_c2_buf(GLOBAL_SIZE_DIM2 __private const int dstChannelC4, __private const int srcChannelC4, __private const int srcChannel, - __private const int bhw, __private const int blockNum, __private const int blockDim) { - const int x = get_global_id(0); //c/2 - const int y = get_global_id(1); //b h w - - UNIFORM_BOUNDRY_CHECK(x, y); + const int ic = get_global_id(0); + const int oc = get_global_id(1); //oc/8 - int idn = x << 1; - int idm = y; - COMPUTE_FLOAT2 bias0 = CONVERT_COMPUTE_FLOAT2(vload2(x, bias)); - COMPUTE_FLOAT2 out0 = bias0; - int input_offset0 = idm * 4; - int out_offset = ((x * 2) / 4 * bhw + idm) * 4 + ((x * 2) % 4); -#ifndef USE_IMAGE - int weight_offset = x * 2 * WEIGHT_STRIDE; - int weight_oc_offset = dstChannelC4 * 4 * WEIGHT_STRIDE; -#endif - - const int loop = (blockDim + CHANNEL_PACK - 1) / CHANNEL_PACK; -#ifdef INPUT_CHANNEL_LEAVE + UNIFORM_BOUNDRY_CHECK_2(ic, oc); + const int oc8 = oc << 3; + + const int loop = (blockDim + 4 - 1) / 4; +#if INPUT_CHANNEL_LEAVES_NUM != 0 const int loop_end = max(loop - 1, 0); #else const int loop_end = loop; #endif - - for (int i = 0; i < blockNum; ++i){ - int kindex = i * dstChannelC4 * 4 * 2; - COMPUTE_FLOAT4 ScaleOffset = CONVERT_COMPUTE_FLOAT4(vload4(x, dequantScaleOffset + kindex)); - for (int j = 0; j < loop_end; ++j) { + COMPUTE_FLOAT8 out0 = CONVERT_COMPUTE_FLOAT8(vload8(0, bias + oc8)); +#ifndef USE_IMAGE + const int weight_offset = oc * srcChannelC4 * 16; +#endif + for (int i = 0; i < blockNum; i++){ + COMPUTE_FLOAT8 scale, offset; + { + COMPUTE_FLOAT16 scaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + oc8 * 2 + i * dstChannelC4 * 8)); + scale = scaleOffset.s02468ace; + offset = scaleOffset.s13579bdf; + } + for (int j = 0; j < loop_end; j++) { int k = i * loop + j; - #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) - int k32 = k << 5; - COMPUTE_FLOAT16 weights00, weights01, weights10, weights11; + COMPUTE_FLOAT8 wei; + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + (k << 2))); + #ifdef USE_IMAGE + uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(k, oc))); + #else + uchar16 charWeightsInt40 = vload16(k, weight + weight_offset); + #endif { - uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn, k))); - uchar16 charWeightsInt41 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn + 1, k))); - char16 charWeights0, charWeights1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights00 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; - weights01 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); - weights10 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; - weights11 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + UCHAR4_TO_CHAR8(charWeightsInt40.s0123, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s0, wei, out0); } { - COMPUTE_FLOAT16 in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + k32)); - COMPUTE_FLOAT16 in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + k32 + 16)); - DOT16X16(in0, weights00, out0.s0);DOT16X16(in1, weights01, out0.s0); - DOT16X16(in0, weights10, out0.s1);DOT16X16(in1, weights11, out0.s1); + UCHAR4_TO_CHAR8(charWeightsInt40.s4567, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s1, wei, out0); } - #else - COMPUTE_FLOAT16 weights0, weights1; - #ifdef USE_IMAGE - weights0 = readWeight(weight, idn, k, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight, idn + 1, k, ScaleOffset.s2, ScaleOffset.s3); - #else - weights0 = readWeight(weight + weight_offset + k * weight_oc_offset, 0, 0, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight + weight_offset + k * weight_oc_offset + WEIGHT_STRIDE, 0, 0, ScaleOffset.s2, ScaleOffset.s3); - #endif { - COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(k, input)); - DOT16X16(in, weights0, out0.s0); - DOT16X16(in, weights1, out0.s1); + UCHAR4_TO_CHAR8(charWeightsInt40.s89ab, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s2, wei, out0); + } + { + UCHAR4_TO_CHAR8(charWeightsInt40.scdef, scale, offset); + out0 = mad((COMPUTE_FLOAT8)in.s3, wei, out0); } - #endif } - #ifdef INPUT_CHANNEL_LEAVE + #if INPUT_CHANNEL_LEAVES_NUM != 0 { int k = i * loop + loop_end; - #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) - int k8 = k << 3; - COMPUTE_FLOAT16 weights00, weights01, weights10, weights11; + int k4 = k << 2; + COMPUTE_FLOAT8 wei; + #ifdef USE_IMAGE + uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(k, oc))); + #else + uchar16 charWeightsInt40 = vload16(k, weight + weight_offset); + #endif { - uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn, k))); - uchar16 charWeightsInt41 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn + 1, k))); - char16 charWeights0, charWeights1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights00 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; - weights01 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); - weights10 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; - weights11 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; - - PADZEROS(k, srcChannel, weights00);PADZEROS(k + 16, srcChannel, weights01); - PADZEROS(k, srcChannel, weights10);PADZEROS(k + 16, srcChannel, weights11); + UCHAR4_TO_CHAR8(charWeightsInt40.s0123, scale, offset); + out0 = mad((COMPUTE_FLOAT8)input[k4], wei, out0); } + #if INPUT_CHANNEL_LEAVES_NUM >= 2 { - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + k8 * 4)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + (k8 + 1) * 4) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + (k8 + 2) * 4) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + (k8 + 3) * 4) : (FLOAT4)0); - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + (k8 + 4) * 4) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + (k8 + 5) * 4) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + (k8 + 6) * 4) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + (k8 + 7) * 4) : (FLOAT4)0); - DOT16X16(in0, weights00, out0.s0);DOT16X16(in1, weights01, out0.s0); - DOT16X16(in0, weights10, out0.s1);DOT16X16(in1, weights11, out0.s1); + UCHAR4_TO_CHAR8(charWeightsInt40.s4567, scale, offset); + out0 = mad((COMPUTE_FLOAT8)input[k4 + 1], wei, out0); } - #else - int k4 = k << 2; - COMPUTE_FLOAT16 weights0, weights1; - #ifdef USE_IMAGE - weights0 = readWeight(weight, idn, k, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight, idn + 1, k, ScaleOffset.s2, ScaleOffset.s3); - #else - weights0 = readWeight(weight + weight_offset + k * weight_oc_offset, 0, 0, ScaleOffset.s0, ScaleOffset.s1); - weights1 = readWeight(weight + weight_offset + k * weight_oc_offset + WEIGHT_STRIDE, 0, 0, ScaleOffset.s2, ScaleOffset.s3); #endif - PADZEROS(k, srcChannel, weights0); - PADZEROS(k, srcChannel, weights1); + #if INPUT_CHANNEL_LEAVES_NUM >= 3 { - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + k4 * 4)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + (k4 + 1) * 4) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + (k4 + 2) * 4) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + (k4 + 3) * 4) : (FLOAT4)0); - DOT16X16(in, weights0, out0.s0); - DOT16X16(in, weights1, out0.s1); + UCHAR4_TO_CHAR8(charWeightsInt40.s89ab, scale, offset); + out0 = mad((COMPUTE_FLOAT8)input[k4 + 2], wei, out0); } #endif } #endif - } - +} #ifdef RELU - out0 = fmax(out0, (COMPUTE_FLOAT2)0); + out0 = fmax(out0, (COMPUTE_FLOAT8)0); #endif #ifdef RELU6 - out0 = clamp(out0, (COMPUTE_FLOAT2)0, (COMPUTE_FLOAT2)6); + out0 = clamp(out0, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); #endif - - vstore2(CONVERT_FLOAT2(out0), 0, output+out_offset); + vstore8(CONVERT_FLOAT8(out0), 0, output + oc8); } -__kernel void gemv_conv_c1_buf(GLOBAL_SIZE_DIM2 +__kernel void gemv_conv_c8_int8_buf(GLOBAL_SIZE_DIM_2 __global const FLOAT* input, #ifdef USE_IMAGE __read_only image2d_t weight, #else -#if (defined USE_LOW_BIT_WEIGHT_INT8) __global const char *weight, -#elif (defined USE_LOW_BIT_WEIGHT_INT4) - __global const uchar *weight, -#endif #endif __global const float *dequantScaleOffset, __global const FLOAT *bias, @@ -435,122 +344,65 @@ __kernel void gemv_conv_c1_buf(GLOBAL_SIZE_DIM2 __private const int dstChannelC4, __private const int srcChannelC4, __private const int srcChannel, - __private const int bhw, __private const int blockNum, __private const int blockDim) { - const int x = get_global_id(0); //c - const int y = get_global_id(1); //b h w - - UNIFORM_BOUNDRY_CHECK(x, y); - int idn = x; - int idm = y; - - COMPUTE_FLOAT bias0 = bias[x]; - COMPUTE_FLOAT out0 = bias0; - - int input_offset0 = idm * 4; - - int out_offset = ((x / 4) * bhw + idm) * 4 + (x % 4); -#ifndef USE_IMAGE - int weight_offset = x * WEIGHT_STRIDE; - int weight_oc_offset = dstChannelC4 * 4 * WEIGHT_STRIDE; -#endif - - const int loop = (blockDim + CHANNEL_PACK - 1) / CHANNEL_PACK; -#ifdef INPUT_CHANNEL_LEAVE + const int ic = get_global_id(0); + const int oc = get_global_id(1); //oc/8 + UNIFORM_BOUNDRY_CHECK_2(ic, oc); + const int oc8 = oc << 3; + const int loop = (blockDim + 2 - 1) / 2; +#if INPUT_CHANNEL_LEAVES_NUM != 0 const int loop_end = max(loop - 1, 0); #else const int loop_end = loop; #endif - - for (int i = 0; i < blockNum; ++i){ - int kindex = i * dstChannelC4 * 4 * 2; - COMPUTE_FLOAT2 ScaleOffset = CONVERT_COMPUTE_FLOAT2(vload2(x, dequantScaleOffset + kindex)); - for (int j = 0; j < loop_end; ++j) { +#ifndef USE_IMAGE + const int weight_offset = oc * srcChannelC4 * 32; +#endif + COMPUTE_FLOAT8 out0 = CONVERT_COMPUTE_FLOAT8(vload8(0, bias + oc8)); + for (int i = 0; i < blockNum; i++){ + COMPUTE_FLOAT16 scale, offset; + { + COMPUTE_FLOAT16 scaleOffset = CONVERT_COMPUTE_FLOAT16(vload16(0, dequantScaleOffset + oc8 * 2 + i * dstChannelC4 * 8)); + scale = (COMPUTE_FLOAT16)(scaleOffset.s02468ace, scaleOffset.s02468ace); + offset = (COMPUTE_FLOAT16)(scaleOffset.s13579bdf, scaleOffset.s13579bdf); + } + for (int j = 0; j < loop_end; j++) { int k = i * loop + j; - #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) - int k32 = k << 5; - COMPUTE_FLOAT16 weights00, weights01; - { - uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn, k))); - char16 charWeights0, charWeights1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights00 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; - weights01 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; - } - { - COMPUTE_FLOAT16 in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + k32)); - COMPUTE_FLOAT16 in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + k32 + 16)); - DOT16X16(in0, weights00, out0);DOT16X16(in1, weights01, out0); - } - #else - COMPUTE_FLOAT16 weights; + COMPUTE_FLOAT2 in = CONVERT_COMPUTE_FLOAT2(vload2(0, input + (k << 1))); #ifdef USE_IMAGE - weights = readWeight(weight, idn, k, ScaleOffset.s0, ScaleOffset.s1); + COMPUTE_FLOAT16 wei = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(k, oc)))) * scale + offset; #else - weights = readWeight(weight + weight_offset + k * weight_oc_offset, 0, 0, ScaleOffset.s0, ScaleOffset.s1); + COMPUTE_FLOAT16 wei = CONVERT_COMPUTE_FLOAT16(vload16(k, weight + weight_offset)) * scale + offset; #endif { - COMPUTE_FLOAT16 in = CONVERT_COMPUTE_FLOAT16(vload16(k, input)); - DOT16X16(in, weights, out0); + out0 = mad((COMPUTE_FLOAT8)in.s0, wei.s01234567, out0); + } + { + out0 = mad((COMPUTE_FLOAT8)in.s1, wei.s89abcdef, out0); } - #endif } - #ifdef INPUT_CHANNEL_LEAVE + #if INPUT_CHANNEL_LEAVES_NUM != 0 { int k = i * loop + loop_end; - #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE) - int k8 = k << 3; - COMPUTE_FLOAT16 weights00, weights01; - { - uchar16 charWeightsInt40 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(idn, k))); - char16 charWeights0, charWeights1; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights00 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; - weights01 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; - - PADZEROS(k, srcChannel, weights00);PADZEROS(k + 16, srcChannel, weights01); - } - { - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + k8 * 4)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + (k8 + 1) * 4) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + (k8 + 2) * 4) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + (k8 + 3) * 4) : (FLOAT4)0); - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + (k8 + 4) * 4) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + (k8 + 5) * 4) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + (k8 + 6) * 4) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + (k8 + 7) * 4) : (FLOAT4)0); - DOT16X16(in0, weights00, out0);DOT16X16(in1, weights01, out0); - } - #else - int k4 = k << 2; - COMPUTE_FLOAT16 weights; #ifdef USE_IMAGE - weights = readWeight(weight, idn, k, ScaleOffset.s0, ScaleOffset.s1); + COMPUTE_FLOAT16 wei = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(k, oc)))) * scale + offset; #else - weights = readWeight(weight + weight_offset + k * weight_oc_offset, 0, 0, ScaleOffset.s0, ScaleOffset.s1); + COMPUTE_FLOAT16 wei = CONVERT_COMPUTE_FLOAT16(vload16(k, weight + weight_offset)) * scale + offset; #endif - PADZEROS(k, srcChannel, weights); { - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + k4 * 4)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + (k4 + 1) * 4) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + (k4 + 2) * 4) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + (k4 + 3) * 4) : (FLOAT4)0); - DOT16X16(in, weights, out0); + out0 = mad((COMPUTE_FLOAT8)input[k << 1], wei.s01234567, out0); } - #endif } #endif } - #ifdef RELU - out0 = fmax(out0, (COMPUTE_FLOAT)0); + out0 = fmax(out0, (COMPUTE_FLOAT8)0); #endif #ifdef RELU6 - out0 = clamp(out0, (COMPUTE_FLOAT)0, (COMPUTE_FLOAT)6); + out0 = clamp(out0, (COMPUTE_FLOAT8)0, (COMPUTE_FLOAT8)6); #endif - output[out_offset] = out0; + vstore8(CONVERT_FLOAT8(out0), 0, output + oc8); } +#endif diff --git a/source/backend/opencl/execution/cl/matmul_params_buf.cl b/source/backend/opencl/execution/cl/matmul_params_buf.cl index a96f2caa7..f028d8728 100644 --- a/source/backend/opencl/execution/cl/matmul_params_buf.cl +++ b/source/backend/opencl/execution/cl/matmul_params_buf.cl @@ -1410,6 +1410,7 @@ void XgemmBatched(const int kSizeM, #endif __global realM* cgm, const int4 batch_offset, // [batch_offset_a, batch_offset_b, batch_offset_c, batch_offset_e] + const int4 base_ptr_offset, // [base_ptr_offset_a, base_ptr_offset_b, base_ptr_offset_c, base_ptr_offset_e] const int4 stride, // [stride_a, stride_b, stride_c, stride_e] /* total_batch -> [loop_y, loop_x] @@ -1421,15 +1422,15 @@ void XgemmBatched(const int kSizeM, const int batch = get_group_id(2); // Sets the offsets - const int a_offset = ((batch / group.w) * group.x + (batch % group.w) / group.x) * batch_offset.x; - const int b_offset = ((batch / group.w) * group.y + (batch % group.w) / group.y) * batch_offset.y; - const int c_offset = batch * batch_offset.z; + const int a_offset = base_ptr_offset.x + ((batch / group.w) * group.x + (batch % group.w) / group.x) * batch_offset.x; + const int b_offset = base_ptr_offset.y + ((batch / group.w) * group.y + (batch % group.w) / group.y) * batch_offset.y; + const int c_offset = base_ptr_offset.z + batch * batch_offset.z; const __global realM* restrict agm_ = &agm[a_offset / VWM]; const __global realN* restrict bgm_ = &bgm[b_offset / VWN]; __global realM* restrict cgm_ = &cgm[c_offset / VWM]; #if BIAS_TYPE > 0 - const int e_offset = ((batch / group.w) * group.z + (batch % group.w) / group.z) * batch_offset.w; + const int e_offset = base_ptr_offset.w + ((batch / group.w) * group.z + (batch % group.w) / group.z) * batch_offset.w; __global realN* restrict egm_ = &egm[e_offset / VWN]; #endif diff --git a/source/backend/opencl/execution/cl/opencl_program.cc b/source/backend/opencl/execution/cl/opencl_program.cc index a809072dc..7ea6914fe 100644 --- a/source/backend/opencl/execution/cl/opencl_program.cc +++ b/source/backend/opencl/execution/cl/opencl_program.cc @@ -1939,7 +1939,6 @@ const char* self_attention_buf = " const int b=z/head_num;\n" " const int hn=z % head_num;\n" " \n" -" const int seq_len_4=(seq_len+3)/4;\n" " const int offset_q=((b*head_num+hn)*head_dim_pack_k+4*hd)*seq_len_piece+4*sl;\n" " if(seq_index>0) {\n" " // fill output_q only\n" @@ -2495,56 +2494,130 @@ const char* gemv_conv1x1_buf = "#ifdef MNN_SUPPORT_FP16\n" "#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" "#endif\n" -"#define GLOBAL_SIZE_DIM2 "" __private int global_size_dim0,__private int global_size_dim1,\n" -"#define UNIFORM_BOUNDRY_CHECK(index0, index1) "" if(index0 >= global_size_dim0 || index1 >= global_size_dim1) { "" return; "" }\n" -"#define UCHAR16_TO_2CHAR16(a, b, c) "" a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; "" a.s8 = (c.s4 >> 4) - 8; a.s9 = (c.s4 & 15) - 8; a.sa = (c.s5 >> 4) - 8; a.sb = (c.s5 & 15) - 8; a.sc = (c.s6 >> 4) - 8; a.sd = (c.s6 & 15) - 8; a.se = (c.s7 >> 4) - 8; a.sf = (c.s7 & 15) - 8; "" b.s0 = (c.s8 >> 4) - 8; b.s1 = (c.s8 & 15) - 8; b.s2 = (c.s9 >> 4) - 8; b.s3 = (c.s9 & 15) - 8; b.s4 = (c.sa >> 4) - 8; b.s5 = (c.sa & 15) - 8; b.s6 = (c.sb >> 4) - 8; b.s7 = (c.sb & 15) - 8; "" b.s8=(c.sc >> 4)-8; b.s9=(c.sc & 15)-8; b.sa=(c.sd >> 4)-8; b.sb=(c.sd & 15)-8; b.sc=(c.se >> 4)-8; b.sd=(c.se & 15)-8; b.se=(c.sf >> 4)-8; b.sf=(c.sf & 15)-8;\n" -"#define UCHAR8_TO_CHAR16(a, c) "" a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; "" a.s8=(c.s4 >> 4)-8; a.s9=(c.s4 & 15)-8; a.sa=(c.s5 >> 4)-8; a.sb=(c.s5 & 15)-8; a.sc=(c.s6 >> 4)-8; a.sd=(c.s6 & 15)-8; a.se=(c.s7 >> 4)-8; a.sf=(c.s7 & 15)-8;\n" -"#define DOT16X16(a, b, c) "" c += dot(a.s0123, b.s0123); "" c += dot(a.s4567, b.s4567); "" c += dot(a.s89ab, b.s89ab); "" c += dot(a.scdef,b.scdef);\n" -"#ifdef INPUT_CHANNEL_LEAVE\n" -" #define PADZEROS(k, channel, data) {"" COMPUTE_FLOAT* ptr = (COMPUTE_FLOAT*)&data; "" int remain = k + 15 - channel; "" for(int r = remain; r >= 0; r--){ "" ptr[15 - r] = 0; "" } "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"#define GLOBAL_SIZE_DIM_2 "" __private int global_size_dim0,__private int global_size_dim1,\n" +"#define UNIFORM_BOUNDRY_CHECK_2(index0, index1) "" if(index0 >= global_size_dim0 || index1 >= global_size_dim1) { "" return; "" }\n" +"#define UCHAR4_TO_CHAR8(b, scale, offset) "" wei.s0 = (COMPUTE_FLOAT)((b.s0 >> 4) - 8); "" wei.s1 = (COMPUTE_FLOAT)((b.s0 & 15) - 8); "" wei.s2 = (COMPUTE_FLOAT)((b.s1 >> 4) - 8); "" wei.s3 = (COMPUTE_FLOAT)((b.s1 & 15) - 8); "" wei.s4 = (COMPUTE_FLOAT)((b.s2 >> 4) - 8); "" wei.s5 = (COMPUTE_FLOAT)((b.s2 & 15) - 8); "" wei.s6 = (COMPUTE_FLOAT)((b.s3 >> 4) - 8); "" wei.s7 = (COMPUTE_FLOAT)((b.s3 & 15) - 8); "" wei=wei*scale+offset;\n" +"#if WGS >= 8\n" +"__kernel void gemv_conv_c8_int4_buf(GLOBAL_SIZE_DIM_2\n" +" __global const FLOAT* input,\n" +"#ifdef USE_IMAGE\n" +" __read_only image2d_t weight,\n" "#else\n" -" #define PADZEROS(k,channel,data)\n" +" __global const uchar *weight,\n" "#endif\n" -"#if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE)\n" -"#define CHANNEL_PACK 32\n" +" __global const float *dequantScaleOffset,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT* output,\n" +" __private const int dstChannelC4,\n" +" __private const int srcChannelC4,\n" +" __private const int srcChannel,\n" +" __private const int blockNum,\n" +" __private const int blockDim) {\n" +" const int lid=get_local_id(0);\n" +" const int oc=get_global_id(1); //oc/8\n" +" const int oc8=oc << 3;\n" +"#if INPUT_CHANNEL_LEAVES_NUM != 0\n" +" const int loop=max((srcChannel+4-1)/4-1,0);\n" "#else\n" -"#define CHANNEL_PACK 16\n" -"#endif\n" -"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" -"#define WEIGHT_STRIDE 16\n" -"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" -"#define WEIGHT_STRIDE 8\n" +" const int loop=(srcChannel+4-1)/4;\n" "#endif\n" -"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" -"#ifdef USE_IMAGE\n" -"inline COMPUTE_FLOAT16 readWeight(__read_only image2d_t weight,int ix,int iy,COMPUTE_FLOAT scale,COMPUTE_FLOAT offset){\n" -" return CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight,SAMPLER,(int2)(ix,iy))))*scale+offset;\n" -"}\n" -"#else\n" -"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" -"inline COMPUTE_FLOAT16 readWeight(__global const char *weight,int ix,int iy,COMPUTE_FLOAT scale,COMPUTE_FLOAT offset){\n" -" return CONVERT_COMPUTE_FLOAT16(vload16(0,weight))*scale+offset;\n" -"}\n" -"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" -"inline COMPUTE_FLOAT16 readWeight(__global const uchar *weight,int ix,int iy,COMPUTE_FLOAT scale,COMPUTE_FLOAT offset){\n" -" uchar16 charWeightsInt40=vload16(0,weight);\n" -" uchar8 charWeightsInt4=vload8(0,weight);\n" -" char16 charWeights=0;\n" -" UCHAR8_TO_CHAR16(charWeights,charWeightsInt4);\n" -" return CONVERT_COMPUTE_FLOAT16(charWeights)*scale+offset;\n" -"}\n" +" __local COMPUTE_FLOAT8 sum[WGS];\n" +" COMPUTE_FLOAT8 out0=0;\n" +"#ifndef USE_IMAGE\n" +" const int weight_offset=oc*srcChannelC4*16;\n" "#endif\n" +" \n" +" for(int j=lid; j= 2\n" +" {\n" +" UCHAR4_TO_CHAR8(charWeightsInt40.s4567,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)input[k4+1],wei,out0);\n" +" }\n" +" #endif\n" +" #if INPUT_CHANNEL_LEAVES_NUM >= 3\n" +" {\n" +" UCHAR4_TO_CHAR8(charWeightsInt40.s89ab,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)input[k4+2],wei,out0);\n" +" }\n" +" #endif\n" +" }\n" "#endif\n" -"__kernel void gemv_conv_c4_buf(GLOBAL_SIZE_DIM2\n" +" sum[lid]=out0;\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" for(int i=WGS/2; i>0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid= 2\n" +" {\n" +" UCHAR4_TO_CHAR8(charWeightsInt40.s4567,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)input[k4+1],wei,out0);\n" " }\n" " #endif\n" +" #if INPUT_CHANNEL_LEAVES_NUM >= 3\n" +" {\n" +" UCHAR4_TO_CHAR8(charWeightsInt40.s89ab,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)input[k4+2],wei,out0);\n" " }\n" " #endif\n" " }\n" -" \n" +" #endif\n" +"}\n" "#ifdef RELU\n" -" out0=fmax(out0,(COMPUTE_FLOAT2)0);\n" +" out0=fmax(out0,(COMPUTE_FLOAT8)0);\n" "#endif\n" "#ifdef RELU6\n" -" out0=clamp(out0,(COMPUTE_FLOAT2)0,(COMPUTE_FLOAT2)6);\n" +" out0=clamp(out0,(COMPUTE_FLOAT8)0,(COMPUTE_FLOAT8)6);\n" "#endif\n" -" vstore2(CONVERT_FLOAT2(out0),0,output+out_offset);\n" +" vstore8(CONVERT_FLOAT8(out0),0,output+oc8);\n" "}\n" -"__kernel void gemv_conv_c1_buf(GLOBAL_SIZE_DIM2\n" +"__kernel void gemv_conv_c8_int8_buf(GLOBAL_SIZE_DIM_2\n" " __global const FLOAT* input,\n" "#ifdef USE_IMAGE\n" " __read_only image2d_t weight,\n" "#else\n" -"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" " __global const char *weight,\n" -"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" -" __global const uchar *weight,\n" -"#endif\n" "#endif\n" " __global const float *dequantScaleOffset,\n" " __global const FLOAT *bias,\n" @@ -2884,121 +2814,67 @@ const char* gemv_conv1x1_buf = " __private const int dstChannelC4,\n" " __private const int srcChannelC4,\n" " __private const int srcChannel,\n" -" __private const int bhw,\n" " __private const int blockNum,\n" " __private const int blockDim) {\n" -" const int x=get_global_id(0); //c\n" -" const int y=get_global_id(1); //b h w\n" -" UNIFORM_BOUNDRY_CHECK(x,y);\n" -" int idn=x;\n" -" int idm=y;\n" -" COMPUTE_FLOAT bias0=bias[x];\n" -" COMPUTE_FLOAT out0=bias0;\n" -" \n" -" int input_offset0=idm*4;\n" -" \n" -" int out_offset=((x/4)*bhw+idm)*4+(x % 4);\n" -"#ifndef USE_IMAGE\n" -" int weight_offset=x*WEIGHT_STRIDE;\n" -" int weight_oc_offset=dstChannelC4*4*WEIGHT_STRIDE;\n" -"#endif\n" -" const int loop=(blockDim+CHANNEL_PACK-1)/CHANNEL_PACK;\n" -"#ifdef INPUT_CHANNEL_LEAVE\n" +" const int ic=get_global_id(0);\n" +" const int oc=get_global_id(1); //oc/8\n" +" UNIFORM_BOUNDRY_CHECK_2(ic,oc);\n" +" const int oc8=oc << 3;\n" +" const int loop=(blockDim+2-1)/2;\n" +"#if INPUT_CHANNEL_LEAVES_NUM != 0\n" " const int loop_end=max(loop-1,0);\n" "#else\n" " const int loop_end=loop;\n" "#endif\n" -" \n" -" for (int i=0; i> 2;\n" -"#ifdef USE_LOW_BIT_WEIGHT_INT4\n" -" const int outputOffset=((x*outputChannelC4*4*8+y*8));\n" -"#ifdef CHANNEL_LEAVE\n" -" for(int i=0; i<8; ++i){\n" -" int index0=y*input_channel+xin+i*2;\n" -" int index1=y*input_channel+xin+i*2+1;\n" -" uchar s0=input_ptr[index0/2];\n" -" uchar s1=input_ptr[index1/2];\n" -" output_ptr[outputOffset+i]=((index0 % 2) == 0 ? (s0 & 0xf0) : (s0 << 4)) | ((index1 % 2) == 0 ? (s1 >> 4) : (s1 & 0x0f));\n" -" }\n" -"#else\n" -" const int inputOffset=(y*input_channel+xin)/2;\n" -" vstore8(convert_char8(vload8(0,input_ptr+inputOffset)),0,output_ptr+outputOffset);\n" -"#endif\n" -"#else\n" -" const int inputOffset=y*input_channel+xin;\n" -" const int outputOffset=(x*outputChannelC4*4+y) << 4;\n" -" vstore16(convert_char16(vload16(0,input_ptr+inputOffset)),0,output_ptr+outputOffset);\n" -"#endif\n" -"}\n" "__kernel void conv2d_1x1_weight_quant_image(GLOBAL_SIZE_2_DIMS\n" "#ifdef USE_LOW_BIT_WEIGHT_INT4\n" " __global const uchar *input_ptr,\n" "#else\n" -" __global const uchar *input_ptr,\n" +" __global const char *input_ptr,\n" "#endif\n" " __write_only image2d_t output,\n" " __private const int input_channel,\n" " __private const int output_channel) {\n" -" int x=get_global_id(0); // ic/32\n" -" int y=get_global_id(1); // oc\n" +" int x=get_global_id(0); // ic/4\n" +" int y=get_global_id(1); // oc/8\n" " DEAL_NON_UNIFORM_DIM2(x,y);\n" +" const int xin=x << 2;\n" +" const int yin=y << 3;\n" "#ifdef USE_LOW_BIT_WEIGHT_INT4\n" -" const int xin=x << 5;\n" -"#ifdef CHANNEL_LEAVE\n" " uchar16 out=0;\n" " uchar *out_ptr=(uchar*)&out;\n" -" for(int i=0; i<16; ++i){\n" -" int index0=y*input_channel+xin+i*2;\n" -" int index1=y*input_channel+xin+i*2+1;\n" +" for(int i=0; i<4; ++i){\n" +" int index0=yin*input_channel+xin+i;\n" +" int index1=(yin+1)*input_channel+xin+i;\n" +" int index2=(yin+2)*input_channel+xin+i;\n" +" int index3=(yin+3)*input_channel+xin+i;\n" +" int index4=(yin+4)*input_channel+xin+i;\n" +" int index5=(yin+5)*input_channel+xin+i;\n" +" int index6=(yin+6)*input_channel+xin+i;\n" +" int index7=(yin+7)*input_channel+xin+i;\n" " uchar s0=input_ptr[index0/2];\n" " uchar s1=input_ptr[index1/2];\n" -" out_ptr[i]=((index0 % 2) == 0 ? (s0 & 0xf0) : (s0 << 4)) | ((index1 % 2) == 0 ? (s1 >> 4) : (s1 & 0x0f));\n" -" }\n" -" write_imagei(output,(int2)(y,x),as_int4(out));\n" -"#else\n" -" const int inputOffset=(y*input_channel+xin)/2;\n" -" write_imagei(output,(int2)(y,x),as_int4(vload16(0,input_ptr+inputOffset)));\n" -"#endif\n" +" uchar s2=input_ptr[index2/2];\n" +" uchar s3=input_ptr[index3/2];\n" +" uchar s4=input_ptr[index4/2];\n" +" uchar s5=input_ptr[index5/2];\n" +" uchar s6=input_ptr[index6/2];\n" +" uchar s7=input_ptr[index7/2];\n" +" out_ptr[i*4]=((index0 % 2) == 0 ? (s0 & 0xf0) : (s0 << 4)) | ((index1 % 2) == 0 ? (s1 >> 4) : (s1 & 0x0f));\n" +" out_ptr[i*4+1]=((index2 % 2) == 0 ? (s2 & 0xf0) : (s2 << 4)) | ((index3 % 2) == 0 ? (s3 >> 4) : (s3 & 0x0f));\n" +" out_ptr[i*4+2]=((index4 % 2) == 0 ? (s4 & 0xf0) : (s4 << 4)) | ((index5 % 2) == 0 ? (s5 >> 4) : (s5 & 0x0f));\n" +" out_ptr[i*4+3]=((index6 % 2) == 0 ? (s6 & 0xf0) : (s6 << 4)) | ((index7 % 2) == 0 ? (s7 >> 4) : (s7 & 0x0f));\n" +" }\n" +" write_imagei(output,(int2)(x,y),as_int4(out));\n" "#else\n" -" const int xin=x << 4;\n" -" const int inputOffset=y*input_channel+xin;\n" -" write_imagei(output,(int2)(y,x),as_int4(vload16(0,input_ptr+inputOffset)));\n" +" const int inputOffset=yin*input_channel+xin;\n" +" char4 s0=vload4(0,input_ptr+inputOffset);\n" +" char4 s1=vload4(0,input_ptr+inputOffset+input_channel);\n" +" char4 s2=vload4(0,input_ptr+inputOffset+input_channel*2);\n" +" char4 s3=vload4(0,input_ptr+inputOffset+input_channel*3);\n" +" char4 s4=vload4(0,input_ptr+inputOffset+input_channel*4);\n" +" char4 s5=vload4(0,input_ptr+inputOffset+input_channel*5);\n" +" char4 s6=vload4(0,input_ptr+inputOffset+input_channel*6);\n" +" char4 s7=vload4(0,input_ptr+inputOffset+input_channel*7);\n" +" char16 out0=(char16)(s0.s0,s1.s0,s2.s0,s3.s0,s4.s0,s5.s0,s6.s0,s7.s0,s0.s1,s1.s1,s2.s1,s3.s1,s4.s1,s5.s1,s6.s1,s7.s1);\n" +" char16 out1=(char16)(s0.s2,s1.s2,s2.s2,s3.s2,s4.s2,s5.s2,s6.s2,s7.s2,s0.s3,s1.s3,s2.s3,s3.s3,s4.s3,s5.s3,s6.s3,s7.s3);\n" +" write_imagei(output,(int2)(x*2,y),as_int4(out0));\n" +" write_imagei(output,(int2)(x*2+1,y),as_int4(out1));\n" "#endif\n" "}\n" -"__kernel void conv2d_1x1_ic_oc_weight_quant_buffer(GLOBAL_SIZE_2_DIMS\n" +"__kernel void conv2d_1x1_weight_quant_buffer(GLOBAL_SIZE_2_DIMS\n" "#ifdef USE_LOW_BIT_WEIGHT_INT4\n" " __global const uchar *input_ptr,\n" -" __global uchar *output_ptr,//(Ci/packCin， Co/packCout,packCin， packCout)\n" "#else\n" " __global const char *input_ptr,\n" -" __global char *output_ptr,//(Ci/packCin， Co/packCout,packCin， packCout)\n" "#endif\n" +" __global char *output_ptr,\n" " __private const int input_channel,\n" -" __private const int output_channel,\n" -" __private const int icPack,\n" -" __private const int ocPack) {\n" -" int x=get_global_id(0); // ic/icPack\n" -" int y=get_global_id(1); // oc/ocPack\n" +" __private const int output_channel) {\n" +" int x=get_global_id(0); // ic/4\n" +" int y=get_global_id(1); // oc/8\n" " DEAL_NON_UNIFORM_DIM2(x,y);\n" -" const int xin=x*icPack;\n" -" const int yin=y*ocPack;\n" -" const int inputChannelC4=(input_channel+icPack-1)/icPack;\n" -" const int outputChannelC4=(output_channel+ocPack-1)/ocPack;\n" +" const int xin=x << 2;\n" +" const int yin=y << 3;\n" +" const int outputChannelC8=(output_channel+7) >> 3;\n" +" const int inputChannelC4=(input_channel+3) >> 2;\n" "#ifdef USE_LOW_BIT_WEIGHT_INT4\n" -" const int inputOffset=(yin*input_channel+xin)/2;\n" -" const int outputOffset=((x*outputChannelC4+y)*icPack*ocPack)/2;\n" -" for(int i=0; i> 4) : (s1 & 0x0f);\n" -" output_ptr[outputOffset+i*(ocPack/2)+j]=s0 | s1;\n" -" }\n" -" }\n" +" uchar s2=input_ptr[index2/2];\n" +" uchar s3=input_ptr[index3/2];\n" +" uchar s4=input_ptr[index4/2];\n" +" uchar s5=input_ptr[index5/2];\n" +" uchar s6=input_ptr[index6/2];\n" +" uchar s7=input_ptr[index7/2];\n" +" out_ptr[i*4]=((index0 % 2) == 0 ? (s0 & 0xf0) : (s0 << 4)) | ((index1 % 2) == 0 ? (s1 >> 4) : (s1 & 0x0f));\n" +" out_ptr[i*4+1]=((index2 % 2) == 0 ? (s2 & 0xf0) : (s2 << 4)) | ((index3 % 2) == 0 ? (s3 >> 4) : (s3 & 0x0f));\n" +" out_ptr[i*4+2]=((index4 % 2) == 0 ? (s4 & 0xf0) : (s4 << 4)) | ((index5 % 2) == 0 ? (s5 >> 4) : (s5 & 0x0f));\n" +" out_ptr[i*4+3]=((index6 % 2) == 0 ? (s6 & 0xf0) : (s6 << 4)) | ((index7 % 2) == 0 ? (s7 >> 4) : (s7 & 0x0f));\n" +" }\n" +" const int outputOffset=(y*inputChannelC4+x)*16;\n" +" vstore16(as_char16(out),0,output_ptr+outputOffset);\n" "#else\n" " const int inputOffset=yin*input_channel+xin;\n" -" const int outputOffset=(x*outputChannelC4+y)*icPack*ocPack;\n" -" for(int i=0; i= out_c_blocks) return;\n" " const int out_w_idx=out_c_w_idx % out_hw.y;\n" " const int out_b_idx=out_b_h_idx/out_hw.x;//equal to in_b_idx\n" " const int out_h_idx=out_b_h_idx % out_hw.x;\n" @@ -14348,11 +14229,14 @@ const char* conv_2d_buf = " __private const int2 dilate_hw,\n" " __private const int out_w_blocks,//generate width's num\n" " __private const int out_c_blocks,\n" -" __private const int out_h_blocks) {\n" +" __private const int out_h_blocks,\n" +" __private const int out_c_base_index\n" +") {\n" " const int out_c_w_idx=get_global_id(0); //c/4 w\n" " const int out_b_h_idx=get_global_id(1); //b h\n" " DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" -" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks+out_c_base_index;\n" +" if(out_c_idx >= out_c_blocks) return;\n" " const int out_w_idx=(out_c_w_idx % out_w_blocks) << 1;\n" " const int out_b_idx=out_b_h_idx/out_hw.x;//equal to in_b_idx\n" " const int out_h_idx=out_b_h_idx % out_hw.x;\n" @@ -14433,11 +14317,14 @@ const char* conv_2d_buf = " __private const int2 dilate_hw,\n" " __private const int out_w_blocks,\n" " __private const int out_c_blocks,\n" -" __private const int out_h_blocks) {\n" +" __private const int out_h_blocks,\n" +" __private const int out_c_base_index\n" +") {\n" " const int out_c_w_idx=get_global_id(0); //c/4 w\n" " const int out_b_h_idx=get_global_id(1); //b h\n" " DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" -" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks+out_c_base_index;\n" +" if(out_c_idx >= out_c_blocks) return;\n" " const int out_w_idx=(out_c_w_idx % out_w_blocks) << 2;\n" " const int out_b_idx=out_b_h_idx/out_hw.x;//equal to in_b_idx\n" " const int out_h_idx=out_b_h_idx % out_hw.x;\n" @@ -14545,11 +14432,14 @@ const char* conv_2d_buf = " __private const int2 dilate_hw,\n" " __private const int out_w_blocks,\n" " __private const int out_c_blocks,\n" -" __private const int out_h_blocks) {\n" +" __private const int out_h_blocks,\n" +" __private const int out_c_base_index\n" +") {\n" " const int out_c_w_idx=get_global_id(0); //c/4 w\n" " const int out_b_h_idx=get_global_id(1); //b h\n" " DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" -" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks+out_c_base_index;\n" +" if(out_c_idx >= out_c_blocks) return;\n" " const int out_w_idx=out_c_w_idx % out_w_blocks;\n" " const int out_b_idx=out_b_h_idx/out_h_blocks;//equal to in_b_idx\n" " const int out_h_idx=(out_b_h_idx % out_h_blocks) << 2;\n" @@ -14668,11 +14558,14 @@ const char* conv_2d_buf = " __private const int2 dilate_hw,\n" " __private const int out_w_blocks,\n" " __private const int out_c_blocks,\n" -" __private const int out_h_blocks) {\n" +" __private const int out_h_blocks,\n" +" __private const int out_c_base_index\n" +") {\n" " const int out_c_w_idx=get_global_id(0); //c/4 w\n" " const int out_b_h_idx=get_global_id(1); //b h\n" " DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" -" const int out_c_idx_0=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_c_idx_0=((out_c_w_idx/out_w_blocks+out_c_base_index) << 1);\n" +" if(out_c_idx_0 >= out_c_blocks) return;\n" " const int out_c_idx_1=out_c_idx_0+1;\n" " const int out_w_idx=out_c_w_idx % out_w_blocks;\n" " const int out_b_idx=out_b_h_idx/out_h_blocks;//equal to in_b_idx\n" @@ -14871,11 +14764,14 @@ const char* conv_2d_buf = " __private const int2 dilate_hw,\n" " __private const int out_w_blocks,\n" " __private const int out_c_blocks,\n" -" __private const int out_h_blocks) {\n" +" __private const int out_h_blocks,\n" +" __private const int out_c_base_index\n" +") {\n" " const int out_c_w_idx=get_global_id(0); //c/4 w\n" " const int out_b_h_idx=get_global_id(1); //b h\n" " DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" -" const int out_c_idx_0=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_c_idx_0=(out_c_w_idx/out_w_blocks+out_c_base_index) << 1;\n" +" if(out_c_idx_0 >= out_c_blocks) return;\n" " const int out_c_idx_1=out_c_idx_0+1;\n" " const int out_w_idx=out_c_w_idx % out_w_blocks;\n" " const int out_b_idx=out_b_h_idx/out_h_blocks;//equal to in_b_idx\n" @@ -15016,11 +14912,14 @@ const char* conv_2d_buf = " __private const int2 dilate_hw,\n" " __private const int out_w_blocks,\n" " __private const int out_c_blocks,\n" -" __private const int out_h_blocks) {\n" +" __private const int out_h_blocks,\n" +" __private const int out_c_base_index\n" +") {\n" " const int out_c_w_idx=get_global_id(0); //c/4 w\n" " const int out_b_h_idx=get_global_id(1); //b h\n" " DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" -" const int out_c_idx_0=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_c_idx_0=(out_c_w_idx/out_w_blocks+out_c_base_index) << 1;\n" +" if(out_c_idx_0 >= out_c_blocks) return;\n" " const int out_c_idx_1=out_c_idx_0+1;\n" " const int out_w_idx=(out_c_w_idx % out_w_blocks) << 2;\n" " const int out_b_idx=out_b_h_idx/out_hw.x;//equal to in_b_idx\n" @@ -19024,6 +18923,7 @@ const char* matmul_params_buf = " #endif\n" " __global realM* cgm,\n" " const int4 batch_offset,// [batch_offset_a,batch_offset_b,batch_offset_c,batch_offset_e]\n" +" const int4 base_ptr_offset,// [base_ptr_offset_a,base_ptr_offset_b,base_ptr_offset_c,base_ptr_offset_e]\n" " const int4 stride,// [stride_a,stride_b,stride_c,stride_e]\n" " /*\n" " total_batch -> [loop_y,loop_x]\n" @@ -19035,15 +18935,15 @@ const char* matmul_params_buf = " const int batch=get_group_id(2);\n" " \n" " // Sets the offsets\n" -" const int a_offset=((batch/group.w)*group.x+(batch % group.w)/group.x)*batch_offset.x;\n" -" const int b_offset=((batch/group.w)*group.y+(batch % group.w)/group.y)*batch_offset.y;\n" -" const int c_offset=batch*batch_offset.z;\n" +" const int a_offset=base_ptr_offset.x+((batch/group.w)*group.x+(batch % group.w)/group.x)*batch_offset.x;\n" +" const int b_offset=base_ptr_offset.y+((batch/group.w)*group.y+(batch % group.w)/group.y)*batch_offset.y;\n" +" const int c_offset=base_ptr_offset.z+batch*batch_offset.z;\n" " const __global realM* restrict agm_=&agm[a_offset/VWM];\n" " const __global realN* restrict bgm_=&bgm[b_offset/VWN];\n" " __global realM* restrict cgm_=&cgm[c_offset/VWM];\n" " \n" " #if BIAS_TYPE>0\n" -" const int e_offset=((batch/group.w)*group.z+(batch % group.w)/group.z)*batch_offset.w;\n" +" const int e_offset=base_ptr_offset.w+((batch/group.w)*group.z+(batch % group.w)/group.z)*batch_offset.w;\n" " __global realN* restrict egm_=&egm[e_offset/VWN];\n" " #endif\n" " \n" @@ -20634,41 +20534,8 @@ const char* gemm_conv1x1_buf = "#endif\n" "#define GLOBAL_SIZE_DIM2 "" __private int global_size_dim0,__private int global_size_dim1,\n" "#define UNIFORM_BOUNDRY_CHECK(index0, index1) "" if(index0 >= global_size_dim0 || index1 >= global_size_dim1) { "" return; "" }\n" -"#define GLOBAL_SIZE_DIM3 "" __private int global_size_dim0,__private int global_size_dim1,__private int global_size_dim2,\n" -"#define UNIFORM_BOUNDRY_CHECK3(index0, index1, index2) "" if(index0 >= global_size_dim0 || index1 >= global_size_dim1 || index2 >= global_size_dim2) { "" return; "" }\n" -"#define UCHAR16_TO_2CHAR16(a, b, c) "" a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; "" a.s8 = (c.s4 >> 4) - 8; a.s9 = (c.s4 & 15) - 8; a.sa = (c.s5 >> 4) - 8; a.sb = (c.s5 & 15) - 8; a.sc = (c.s6 >> 4) - 8; a.sd = (c.s6 & 15) - 8; a.se = (c.s7 >> 4) - 8; a.sf = (c.s7 & 15) - 8; "" b.s0 = (c.s8 >> 4) - 8; b.s1 = (c.s8 & 15) - 8; b.s2 = (c.s9 >> 4) - 8; b.s3 = (c.s9 & 15) - 8; b.s4 = (c.sa >> 4) - 8; b.s5 = (c.sa & 15) - 8; b.s6 = (c.sb >> 4) - 8; b.s7 = (c.sb & 15) - 8; "" b.s8=(c.sc >> 4)-8; b.s9=(c.sc & 15)-8; b.sa=(c.sd >> 4)-8; b.sb=(c.sd & 15)-8; b.sc=(c.se >> 4)-8; b.sd=(c.se & 15)-8; b.se=(c.sf >> 4)-8; b.sf=(c.sf & 15)-8;\n" -"#define UCHAR8_TO_CHAR16(a, c) "" a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; "" a.s8=(c.s4 >> 4)-8; a.s9=(c.s4 & 15)-8; a.sa=(c.s5 >> 4)-8; a.sb=(c.s5 & 15)-8; a.sc=(c.s6 >> 4)-8; a.sd=(c.s6 & 15)-8; a.se=(c.s7 >> 4)-8; a.sf=(c.s7 & 15)-8;\n" -"#define DOT16X16(a, b, c) "" c += dot(a.s0123, b.s0123); "" c += dot(a.s4567, b.s4567); "" c += dot(a.s89ab, b.s89ab); "" c += dot(a.scdef,b.scdef);\n" -"#if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE)\n" -"#define CHANNEL_PACK 32\n" -"#else\n" -"#define CHANNEL_PACK 16\n" -"#endif\n" -"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" -"#define WEIGHT_STRIDE 16\n" -"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" -"#define WEIGHT_STRIDE 8\n" -"#endif\n" +"#define UCHAR4_TO_CHAR8(a, c) "" a.s0=(c.s0 >> 4)-8; a.s1=(c.s0 & 15)-8; a.s2=(c.s1 >> 4)-8; a.s3=(c.s1 & 15)-8; a.s4=(c.s2 >> 4)-8; a.s5=(c.s2 & 15)-8; a.s6=(c.s3 >> 4)-8; a.s7=(c.s3 & 15)-8;\n" "__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" -"#ifdef USE_IMAGE\n" -"inline COMPUTE_FLOAT16 readWeight(__read_only image2d_t weight,int ix,int iy,COMPUTE_FLOAT scale,COMPUTE_FLOAT offset){\n" -" return CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight,SAMPLER,(int2)(ix,iy))))*scale+offset;\n" -"}\n" -"#else\n" -"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" -"inline COMPUTE_FLOAT16 readWeight(__global const char *weight,int ix,int iy,COMPUTE_FLOAT scale,COMPUTE_FLOAT offset){\n" -" return CONVERT_COMPUTE_FLOAT16(vload16(0,weight))*scale+offset;\n" -"}\n" -"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" -"inline COMPUTE_FLOAT16 readWeight(__global const uchar *weight,int ix,int iy,COMPUTE_FLOAT scale,COMPUTE_FLOAT offset){\n" -" uchar16 charWeightsInt40=vload16(0,weight);\n" -" uchar8 charWeightsInt4=vload8(0,weight);\n" -" char16 charWeights=0;\n" -" UCHAR8_TO_CHAR16(charWeights,charWeightsInt4);\n" -" return CONVERT_COMPUTE_FLOAT16(charWeights)*scale+offset;\n" -"}\n" -"#endif\n" -"#endif\n" "__kernel void inverse_quant_weight(GLOBAL_SIZE_DIM2\n" " #ifdef USE_IMAGE\n" " __read_only image2d_t weight,\n" @@ -20681,650 +20548,612 @@ const char* gemm_conv1x1_buf = " #endif\n" " __global const float *dequantScaleOffset,\n" " __global FLOAT* output,\n" +" __private const int inputChannel4Align,\n" " __private const int outputChannelAlign,\n" " __private const int outputChannel4Align,\n" " __private const int blockDim){\n" " const int x=get_global_id(0); //ic\n" " const int y=get_global_id(1); //oc\n" " UNIFORM_BOUNDRY_CHECK(x,y);\n" -" #if defined(USE_LOW_BIT_WEIGHT_INT4) && defined(USE_IMAGE)\n" " \n" -" const int ic=x << 5;\n" -" const int oc=y << 2;\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" const int ic=x << 2;\n" +" const int oc=y << 3;\n" " const int output_offset=ic*outputChannelAlign+oc;\n" " int kindex=(ic/blockDim)*outputChannel4Align*2;\n" -" COMPUTE_FLOAT8 ScaleOffset=CONVERT_COMPUTE_FLOAT8(vload8(0,dequantScaleOffset+kindex+oc*2));\n" -" COMPUTE_FLOAT16 weights00,weights01,weights10,weights11,weights20,weights21,weights30,weights31;\n" -" {\n" -" uchar16 charWeightsInt40=as_uchar16(read_imagei(weight,SAMPLER,(int2)(oc,x)));\n" -" uchar16 charWeightsInt41=as_uchar16(read_imagei(weight,SAMPLER,(int2)(oc+1,x)));\n" -" uchar16 charWeightsInt42=as_uchar16(read_imagei(weight,SAMPLER,(int2)(oc+2,x)));\n" -" uchar16 charWeightsInt43=as_uchar16(read_imagei(weight,SAMPLER,(int2)(oc+3,x)));\n" -" char16 charWeights0,charWeights1;\n" -" UCHAR16_TO_2CHAR16(charWeights0,charWeights1,charWeightsInt40);\n" -" weights00=CONVERT_COMPUTE_FLOAT16(charWeights0)*ScaleOffset.s0+ScaleOffset.s1;\n" -" weights01=CONVERT_COMPUTE_FLOAT16(charWeights1)*ScaleOffset.s0+ScaleOffset.s1;\n" -" UCHAR16_TO_2CHAR16(charWeights0,charWeights1,charWeightsInt41);\n" -" weights10=CONVERT_COMPUTE_FLOAT16(charWeights0)*ScaleOffset.s2+ScaleOffset.s3;\n" -" weights11=CONVERT_COMPUTE_FLOAT16(charWeights1)*ScaleOffset.s2+ScaleOffset.s3;\n" -" UCHAR16_TO_2CHAR16(charWeights0,charWeights1,charWeightsInt42);\n" -" weights20=CONVERT_COMPUTE_FLOAT16(charWeights0)*ScaleOffset.s4+ScaleOffset.s5;\n" -" weights21=CONVERT_COMPUTE_FLOAT16(charWeights1)*ScaleOffset.s4+ScaleOffset.s5;\n" -" UCHAR16_TO_2CHAR16(charWeights0,charWeights1,charWeightsInt43);\n" -" weights30=CONVERT_COMPUTE_FLOAT16(charWeights0)*ScaleOffset.s6+ScaleOffset.s7;\n" -" weights31=CONVERT_COMPUTE_FLOAT16(charWeights1)*ScaleOffset.s6+ScaleOffset.s7;\n" -" }\n" -" COMPUTE_FLOAT *weights00_ptr=(COMPUTE_FLOAT *)&weights00;\n" -" COMPUTE_FLOAT *weights10_ptr=(COMPUTE_FLOAT *)&weights10;\n" -" COMPUTE_FLOAT *weights20_ptr=(COMPUTE_FLOAT *)&weights20;\n" -" COMPUTE_FLOAT *weights30_ptr=(COMPUTE_FLOAT *)&weights30;\n" -" COMPUTE_FLOAT *weights01_ptr=(COMPUTE_FLOAT *)&weights01;\n" -" COMPUTE_FLOAT *weights11_ptr=(COMPUTE_FLOAT *)&weights11;\n" -" COMPUTE_FLOAT *weights21_ptr=(COMPUTE_FLOAT *)&weights21;\n" -" COMPUTE_FLOAT *weights31_ptr=(COMPUTE_FLOAT *)&weights31;\n" -" #pragma unroll\n" -" for (int i=0; i<16; ++i){\n" -" FLOAT4 out=CONVERT_FLOAT4((COMPUTE_FLOAT4)(weights00_ptr[i],weights10_ptr[i],weights20_ptr[i],weights30_ptr[i]));\n" -" vstore4(out,0,output+output_offset+i*outputChannelAlign);\n" -" }\n" -" #pragma unroll\n" -" for (int i=0; i<16; ++i){\n" -" FLOAT4 out=CONVERT_FLOAT4((COMPUTE_FLOAT4)(weights01_ptr[i],weights11_ptr[i],weights21_ptr[i],weights31_ptr[i]));\n" -" vstore4(out,0,output+output_offset+(i+16)*outputChannelAlign);\n" +" COMPUTE_FLOAT8 scale,offset;\n" +" {\n" +" COMPUTE_FLOAT16 ScaleOffset=CONVERT_COMPUTE_FLOAT16(vload16(0,dequantScaleOffset+kindex+oc*2));\n" +" scale=ScaleOffset.s02468ace;\n" +" offset=ScaleOffset.s13579bdf;\n" " }\n" +" COMPUTE_FLOAT8 weights0,weights1,weights2,weights3;\n" +" {\n" +" #ifdef USE_IMAGE\n" +" uchar16 charWeightsInt40=as_uchar16(read_imagei(weight,SAMPLER,(int2)(x,y)));\n" " #else\n" -" const int ic=x << 4;\n" -" const int oc=y << 2;\n" -"#ifndef USE_IMAGE\n" -" #if (defined USE_LOW_BIT_WEIGHT_INT4)\n" -" int weight_offset=oc*8;\n" -" int weight_oc_offset=outputChannel4Align*8;\n" -" int weight_stride=8;\n" -" #else\n" -" int weight_offset=oc*16;\n" -" int weight_oc_offset=outputChannel4Align*16;\n" -" int weight_stride=16;\n" +" uchar16 charWeightsInt40=vload16(x,weight+y*inputChannel4Align*4);\n" " #endif\n" -"#endif\n" +" char8 charWeights0;\n" +" UCHAR4_TO_CHAR8(charWeights0,charWeightsInt40.s0123);\n" +" weights0=CONVERT_COMPUTE_FLOAT8(charWeights0)*scale+offset;\n" +" \n" +" UCHAR4_TO_CHAR8(charWeights0,charWeightsInt40.s4567);\n" +" weights1=CONVERT_COMPUTE_FLOAT8(charWeights0)*scale+offset;\n" +" \n" +" UCHAR4_TO_CHAR8(charWeights0,charWeightsInt40.s89ab);\n" +" weights2=CONVERT_COMPUTE_FLOAT8(charWeights0)*scale+offset;\n" +" \n" +" UCHAR4_TO_CHAR8(charWeights0,charWeightsInt40.scdef);\n" +" weights3=CONVERT_COMPUTE_FLOAT8(charWeights0)*scale+offset;\n" +" }\n" +" vstore8(weights0,0,output+output_offset);\n" +" vstore8(weights1,0,output+output_offset+outputChannelAlign);\n" +" vstore8(weights2,0,output+output_offset+2*outputChannelAlign);\n" +" vstore8(weights3,0,output+output_offset+3*outputChannelAlign);\n" +"#else\n" +" const int ic=x << 1;\n" +" const int oc=y << 3;\n" " const int output_offset=ic*outputChannelAlign+oc;\n" " int kindex=(ic/blockDim)*outputChannel4Align*2;\n" -" COMPUTE_FLOAT8 ScaleOffset=CONVERT_COMPUTE_FLOAT8(vload8(0,dequantScaleOffset+kindex+oc*2));\n" +" COMPUTE_FLOAT8 scale,offset;\n" +" {\n" +" COMPUTE_FLOAT16 ScaleOffset=CONVERT_COMPUTE_FLOAT16(vload16(0,dequantScaleOffset+kindex+oc*2));\n" +" scale=ScaleOffset.s02468ace;\n" +" offset=ScaleOffset.s13579bdf;\n" +" }\n" +" COMPUTE_FLOAT8 weights0,weights1;\n" +" {\n" " #ifdef USE_IMAGE\n" -" COMPUTE_FLOAT16 weights0=readWeight(weight,oc,x,ScaleOffset.s0,ScaleOffset.s1);\n" -" COMPUTE_FLOAT16 weights1=readWeight(weight,oc+1,x,ScaleOffset.s2,ScaleOffset.s3);\n" -" COMPUTE_FLOAT16 weights2=readWeight(weight,oc+2,x,ScaleOffset.s4,ScaleOffset.s5);\n" -" COMPUTE_FLOAT16 weights3=readWeight(weight,oc+3,x,ScaleOffset.s6,ScaleOffset.s7);\n" +" COMPUTE_FLOAT16 wei=CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight,SAMPLER,(int2)(x,y))));\n" " #else\n" -" COMPUTE_FLOAT16 weights0=readWeight(weight+weight_offset+x*weight_oc_offset,0,0,ScaleOffset.s0,ScaleOffset.s1);\n" -" COMPUTE_FLOAT16 weights1=readWeight(weight+weight_offset+x*weight_oc_offset+weight_stride,0,0,ScaleOffset.s2,ScaleOffset.s3);\n" -" COMPUTE_FLOAT16 weights2=readWeight(weight+weight_offset+x*weight_oc_offset+2*weight_stride,0,0,ScaleOffset.s4,ScaleOffset.s5);\n" -" COMPUTE_FLOAT16 weights3=readWeight(weight+weight_offset+x*weight_oc_offset+3*weight_stride,0,0,ScaleOffset.s6,ScaleOffset.s7);\n" -" #endif\n" -" COMPUTE_FLOAT *weights0_ptr=(COMPUTE_FLOAT*)&weights0;\n" -" COMPUTE_FLOAT *weights1_ptr=(COMPUTE_FLOAT*)&weights1;\n" -" COMPUTE_FLOAT *weights2_ptr=(COMPUTE_FLOAT*)&weights2;\n" -" COMPUTE_FLOAT *weights3_ptr=(COMPUTE_FLOAT*)&weights3;\n" -" #pragma unroll\n" -" for (int i=0; i<16; ++i){\n" -" FLOAT4 out=CONVERT_FLOAT4((COMPUTE_FLOAT4)(weights0_ptr[i],weights1_ptr[i],weights2_ptr[i],weights3_ptr[i]));\n" -" vstore4(out,0,output+output_offset+i*outputChannelAlign);\n" -" }\n" +" COMPUTE_FLOAT16 wei=CONVERT_COMPUTE_FLOAT16(vload16(x,weight+y*inputChannel4Align*8));\n" " #endif\n" +" weights0=wei.s01234567*scale+offset;\n" +" weights1=wei.s89abcdef*scale+offset;\n" +" }\n" +" vstore8(weights0,0,output+output_offset);\n" +" vstore8(weights1,0,output+output_offset+outputChannelAlign);\n" +"#endif\n" "}\n" -"__kernel void reshape_nchw4_nhwc4(GLOBAL_SIZE_DIM2\n" -"__global const FLOAT* input,\n" -"__global FLOAT* output,\n" -"__private const int bhw,\n" -"__private const int channel,\n" -"__private const int channelAlign){\n" -" const int x=get_global_id(0); //c\n" -" const int y=get_global_id(1); //bhw\n" -" UNIFORM_BOUNDRY_CHECK(x,y);\n" -" \n" -" const int x4=x << 2;\n" -" const int y4=y << 2;\n" -" const int input_offset=(x*bhw+y4)*4;\n" -" FLOAT4 in0=vload4(0,input+input_offset);\n" -" FLOAT4 in1=(y4+1= channel){\n" -" FLOAT *in0_ptr=(FLOAT*)&in0;\n" -" FLOAT *in1_ptr=(FLOAT*)&in1;\n" -" FLOAT *in2_ptr=(FLOAT*)&in2;\n" -" FLOAT *in3_ptr=(FLOAT*)&in3;\n" -" int remain=x4+3-channel;\n" -" for(int i=remain; i >= 0; i--){\n" -" in0_ptr[3-i]=0;\n" -" in1_ptr[3-i]=0;\n" -" in2_ptr[3-i]=0;\n" -" in3_ptr[3-i]=0;\n" -" }\n" -" }\n" -"#endif\n" -" \n" -"#ifdef FORMAT_CNHW\n" -" int idx=x/4;\n" -" int idy=x % 4;\n" -" const int bhw4=(bhw+3)/4*4;\n" -" int output_offset=((idx*bhw4+y4)*4+idy)*4; // [c/16 b 4 4]\n" -" vstore4(in0,0,output+output_offset);\n" -" vstore4(in1,0,output+output_offset+16);\n" -" vstore4(in2,0,output+output_offset+32);\n" -" vstore4(in3,0,output+output_offset+48);\n" -"#else\n" -" FLOAT16 out=(FLOAT16)(in0.s0,in1.s0,in2.s0,in3.s0,in0.s1,in1.s1,in2.s1,in3.s1,in0.s2,in1.s2,in2.s2,in3.s2,in0.s3,in1.s3,in2.s3,in3.s3);\n" -" const int output_offset=(y*channelAlign+x4)*4;\n" -" vstore16(out,0,output+output_offset);\n" -"#endif\n" -"}\n" -"__kernel void reshape_nhwc4_nchw4(GLOBAL_SIZE_DIM2\n" -"__global const FLOAT* input,\n" -"__global FLOAT* output,\n" -"__private const int bhw,\n" -"__private const int channelAlign){\n" -" const int x=get_global_id(0); //c\n" -" const int y=get_global_id(1); //bhw\n" -" UNIFORM_BOUNDRY_CHECK(x,y);\n" -" \n" -" const int x4=x << 2;\n" -" const int y4=y << 2;\n" -" const int output_offset=(x*bhw+y4)*4;\n" -" \n" -" const int input_offset=(y*channelAlign+x4)*4;\n" -" FLOAT16 in=vload16(0,input+input_offset);\n" -" \n" -" FLOAT4 out0=(FLOAT4)(in.s0,in.s4,in.s8,in.sc);\n" -" FLOAT4 out1=(FLOAT4)(in.s1,in.s5,in.s9,in.sd);\n" -" FLOAT4 out2=(FLOAT4)(in.s2,in.s6,in.sa,in.se);\n" -" FLOAT4 out3=(FLOAT4)(in.s3,in.s7,in.sb,in.sf);\n" -" vstore4(out0,0,output+output_offset);\n" -" if(y4+1 >= bhw) return;\n" -" vstore4(out1,0,output+output_offset+4);\n" -" if(y4+2 >= bhw) return;\n" -" vstore4(out2,0,output+output_offset+8);\n" -" if(y4+3 >= bhw) return;\n" -" vstore4(out3,0,output+output_offset+12);\n" -"}\n" -"__kernel void gemm_b4_c4_buf(GLOBAL_SIZE_DIM2\n" +"#define UCHAR4_TO_FLOAT8(b, scale, offset) "" wei.s0 = (COMPUTE_FLOAT)((b.s0 >> 4) - 8); "" wei.s1 = (COMPUTE_FLOAT)((b.s0 & 15) - 8); "" wei.s2 = (COMPUTE_FLOAT)((b.s1 >> 4) - 8); "" wei.s3 = (COMPUTE_FLOAT)((b.s1 & 15) - 8); "" wei.s4 = (COMPUTE_FLOAT)((b.s2 >> 4) - 8); "" wei.s5 = (COMPUTE_FLOAT)((b.s2 & 15) - 8); "" wei.s6 = (COMPUTE_FLOAT)((b.s3 >> 4) - 8); "" wei.s7 = (COMPUTE_FLOAT)((b.s3 & 15) - 8); "" wei=wei*scale+offset;\n" +"__kernel void gemm_b4_c8_int4_buf(GLOBAL_SIZE_DIM2\n" " __global const FLOAT* input,\n" "#ifdef USE_IMAGE\n" " __read_only image2d_t weight,\n" "#else\n" -"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" -" __global const char *weight,\n" -"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" " __global const uchar *weight,\n" "#endif\n" -"#endif\n" " __global const float *dequantScaleOffset,\n" " __global const FLOAT *bias,\n" " __global FLOAT* output,\n" -" __private const int bhw4,\n" +" __private const int bhw,\n" " __private const int dstChannelAlign,\n" " __private const int srcChannelAlign,\n" " __private const int blockNum,\n" " __private const int blockDim) {\n" -" const int x=get_global_id(0); //c\n" -" const int y=get_global_id(1); //b\n" +" const int x=get_global_id(0); //b/4\n" +" const int y=get_global_id(1); //c/8\n" " UNIFORM_BOUNDRY_CHECK(x,y);\n" -" const int out_c_idx=x << 2;\n" -" const int out_b_idx=y << 2;\n" -" COMPUTE_FLOAT4 bias0=CONVERT_COMPUTE_FLOAT4(vload4(0,bias+out_c_idx));\n" -" COMPUTE_FLOAT4 out=(COMPUTE_FLOAT4)bias0.s0;\n" -" COMPUTE_FLOAT4 out1=(COMPUTE_FLOAT4)bias0.s1,out2=(COMPUTE_FLOAT4)bias0.s2,out3=(COMPUTE_FLOAT4)bias0.s3;\n" -"#ifdef FORMAT_CNHW\n" -" int input_offset=out_b_idx*16;\n" -"#else\n" -" int input_offset=out_b_idx*srcChannelAlign;\n" -"#endif\n" -" int out_offset=out_b_idx*dstChannelAlign+out_c_idx*4;\n" " \n" +" const int out_b_idx=x << 2;\n" +" const int out_c_idx=y << 1;\n" +" COMPUTE_FLOAT8 out0=CONVERT_FLOAT8(vload8(0,bias+(out_c_idx << 2)));\n" +" COMPUTE_FLOAT8 out1=out0;\n" +" COMPUTE_FLOAT8 out2=out0;\n" +" COMPUTE_FLOAT8 out3=out0;\n" +" \n" +" const int bhw4=bhw << 2;\n" +" const int input_offset=out_b_idx*4;\n" +" int out_offset=out_c_idx*bhw4+out_b_idx*4;\n" "#ifndef USE_IMAGE\n" -" int weight_offset=out_c_idx*WEIGHT_STRIDE;\n" -" int weight_oc_offset=dstChannelAlign*WEIGHT_STRIDE;\n" +" const int weight_offset=y*srcChannelAlign*4;\n" "#endif\n" -" const int loop=(blockDim+CHANNEL_PACK-1)/CHANNEL_PACK;\n" -" \n" +" const int loop=(blockDim+4-1)/4;\n" +"#if INPUT_CHANNEL_LEAVES_NUM != 0\n" +" const int loop_end=max(loop-1,0);\n" +"#else\n" +" const int loop_end=loop;\n" +"#endif\n" +"#if INPUT_BATCH_LEAVES_NUM != 0\n" +" if(out_b_idx+3 >= bhw){\n" " for (int i=0; i= 2\n" +" COMPUTE_FLOAT4 in1=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+k*bhw4+4));\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" COMPUTE_FLOAT4 in2=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+k*bhw4+8));\n" +" #endif\n" +" {\n" +" UCHAR4_TO_FLOAT8(charWeightsInt40.s0123,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)in0.s0,wei,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s0,wei,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s0,wei,out2);\n" +" #endif\n" " }\n" -" #pragma unroll\n" -" for (int i=0; i<16; ++i){\n" -" COMPUTE_FLOAT4 in=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+(k32+i+16)*4));\n" -" out=mad(in,weights01_ptr[i],out);\n" -" out1=mad(in,weights11_ptr[i],out1);\n" -" out2=mad(in,weights21_ptr[i],out2);\n" -" out3=mad(in,weights31_ptr[i],out3);\n" +" {\n" +" UCHAR4_TO_FLOAT8(charWeightsInt40.s4567,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)in0.s1,wei,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s1,wei,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s1,wei,out2);\n" +" #endif\n" " }\n" +" {\n" +" UCHAR4_TO_FLOAT8(charWeightsInt40.s89ab,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)in0.s2,wei,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s2,wei,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s2,wei,out2);\n" +" #endif\n" +" }\n" +" {\n" +" UCHAR4_TO_FLOAT8(charWeightsInt40.scdef,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)in0.s3,wei,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s3,wei,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s3,wei,out2);\n" +" #endif\n" +" }\n" +" }\n" +" #if INPUT_CHANNEL_LEAVES_NUM != 0\n" +" {\n" +" int k=i*loop+loop_end;\n" +" COMPUTE_FLOAT8 wei;\n" +" COMPUTE_FLOAT4 in0=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+k*bhw4));\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" COMPUTE_FLOAT4 in1=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+k*bhw4+4));\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" COMPUTE_FLOAT4 in2=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+k*bhw4+8));\n" " #endif\n" -" #else\n" -" COMPUTE_FLOAT16 weights0,weights1,weights2,weights3;\n" " #ifdef USE_IMAGE\n" -" weights0=readWeight(weight,out_c_idx,k,ScaleOffset.s0,ScaleOffset.s1);\n" -" weights1=readWeight(weight,out_c_idx+1,k,ScaleOffset.s2,ScaleOffset.s3);\n" -" weights2=readWeight(weight,out_c_idx+2,k,ScaleOffset.s4,ScaleOffset.s5);\n" -" weights3=readWeight(weight,out_c_idx+3,k,ScaleOffset.s6,ScaleOffset.s7);\n" +" uchar16 charWeightsInt40=as_uchar16(read_imagei(weight,SAMPLER,(int2)(k,y)));\n" " #else\n" -" weights0=readWeight(weight+weight_offset+k*weight_oc_offset,0,0,ScaleOffset.s0,ScaleOffset.s1);\n" -" weights1=readWeight(weight+weight_offset+k*weight_oc_offset+WEIGHT_STRIDE,0,0,ScaleOffset.s2,ScaleOffset.s3);\n" -" weights2=readWeight(weight+weight_offset+k*weight_oc_offset+2*WEIGHT_STRIDE,0,0,ScaleOffset.s4,ScaleOffset.s5);\n" -" weights3=readWeight(weight+weight_offset+k*weight_oc_offset+3*WEIGHT_STRIDE,0,0,ScaleOffset.s6,ScaleOffset.s7);\n" -" #endif\n" -" #ifdef FORMAT_CNHW\n" -" COMPUTE_FLOAT16 in=CONVERT_COMPUTE_FLOAT16(vload16(0,input+input_offset+k*bhw4*16));\n" -" DOT16X16(in,weights0,out.s0);\n" -" DOT16X16(in,weights1,out1.s0);\n" -" DOT16X16(in,weights2,out2.s0);\n" -" DOT16X16(in,weights3,out3.s0);\n" -" in=CONVERT_COMPUTE_FLOAT16(vload16(0,input+input_offset+k*bhw4*16+16));\n" -" DOT16X16(in,weights0,out.s1);\n" -" DOT16X16(in,weights1,out1.s1);\n" -" DOT16X16(in,weights2,out2.s1);\n" -" DOT16X16(in,weights3,out3.s1);\n" -" in=CONVERT_COMPUTE_FLOAT16(vload16(0,input+input_offset+k*bhw4*16+32));\n" -" DOT16X16(in,weights0,out.s2);\n" -" DOT16X16(in,weights1,out1.s2);\n" -" DOT16X16(in,weights2,out2.s2);\n" -" DOT16X16(in,weights3,out3.s2);\n" -" in=CONVERT_COMPUTE_FLOAT16(vload16(0,input+input_offset+k*bhw4*16+48));\n" -" DOT16X16(in,weights0,out.s3);\n" -" DOT16X16(in,weights1,out1.s3);\n" -" DOT16X16(in,weights2,out2.s3);\n" -" DOT16X16(in,weights3,out3.s3);\n" -" #else\n" -" int k16=k << 4;\n" -" COMPUTE_FLOAT *weights0_ptr=(COMPUTE_FLOAT *)&weights0;\n" -" COMPUTE_FLOAT *weights1_ptr=(COMPUTE_FLOAT *)&weights1;\n" -" COMPUTE_FLOAT *weights2_ptr=(COMPUTE_FLOAT *)&weights2;\n" -" COMPUTE_FLOAT *weights3_ptr=(COMPUTE_FLOAT *)&weights3;\n" -" #pragma unroll\n" -" for (int i=0; i<16; ++i){\n" -" COMPUTE_FLOAT4 in=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+(k16+i)*4));\n" -" out=mad(in,weights0_ptr[i],out);\n" -" out1=mad(in,weights1_ptr[i],out1);\n" -" out2=mad(in,weights2_ptr[i],out2);\n" -" out3=mad(in,weights3_ptr[i],out3);\n" +" uchar16 charWeightsInt40=vload16(k,weight+weight_offset);\n" +" #endif\n" +" {\n" +" UCHAR4_TO_FLOAT8(charWeightsInt40.s0123,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)in0.s0,wei,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s0,wei,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s0,wei,out2);\n" +" #endif\n" " }\n" +" #if INPUT_CHANNEL_LEAVES_NUM >= 2\n" +" {\n" +" UCHAR4_TO_FLOAT8(charWeightsInt40.s4567,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)in0.s1,wei,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s1,wei,out1);\n" " #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s1,wei,out2);\n" " #endif\n" " }\n" +" #endif\n" +" #if INPUT_CHANNEL_LEAVES_NUM >= 3\n" +" {\n" +" UCHAR4_TO_FLOAT8(charWeightsInt40.s89ab,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)in0.s2,wei,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s2,wei,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s2,wei,out2);\n" +" #endif\n" " }\n" -"#ifdef RELU\n" -" out=fmax(out,(COMPUTE_FLOAT4)0);\n" -" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" -" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" -" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" -"#endif\n" -"#ifdef RELU6\n" -" out=clamp(out,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" -" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" -" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" -" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" -"#endif\n" -" vstore4(CONVERT_FLOAT4(out),0,output+out_offset);\n" -" vstore4(CONVERT_FLOAT4(out1),0,output+out_offset+4);\n" -" vstore4(CONVERT_FLOAT4(out2),0,output+out_offset+8);\n" -" vstore4(CONVERT_FLOAT4(out3),0,output+out_offset+12);\n" -"}\n" -"__kernel void gemm_b4_c2_buf(GLOBAL_SIZE_DIM2\n" -" __global const FLOAT* input,\n" -"#ifdef USE_IMAGE\n" -" __read_only image2d_t weight,\n" -"#else\n" -"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" -" __global const char *weight,\n" -"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" -" __global const uchar *weight,\n" -"#endif\n" -"#endif\n" -" __global const float *dequantScaleOffset,\n" -" __global const FLOAT *bias,\n" -" __global FLOAT* output,\n" -" __private const int bhw4,\n" -" __private const int dstChannelAlign,\n" -" __private const int srcChannelAlign,\n" -" __private const int blockNum,\n" -" __private const int blockDim) {\n" -" const int x=get_global_id(0); //c\n" -" const int y=get_global_id(1); //b\n" -" UNIFORM_BOUNDRY_CHECK(x,y);\n" -" const int out_c_idx=x << 1;\n" -" const int out_b_idx=y << 2;\n" -" COMPUTE_FLOAT2 bias0=CONVERT_COMPUTE_FLOAT2(vload2(0,bias+out_c_idx));\n" -" COMPUTE_FLOAT4 out=(COMPUTE_FLOAT4)bias0.s0;\n" -" COMPUTE_FLOAT4 out1=(COMPUTE_FLOAT4)bias0.s1;\n" -" \n" -"#ifdef FORMAT_CNHW\n" -" int input_offset=out_b_idx*16;\n" -"#else\n" -" int input_offset=out_b_idx*srcChannelAlign;\n" -"#endif\n" -" int out_offset=out_b_idx*dstChannelAlign+out_c_idx*4;\n" -" \n" -"#ifndef USE_IMAGE\n" -" int weight_offset=out_c_idx*WEIGHT_STRIDE;\n" -" int weight_oc_offset=dstChannelAlign*WEIGHT_STRIDE;\n" +" #endif\n" +" }\n" +" #endif\n" +" }\n" +" } else {\n" "#endif\n" -" const int loop=(blockDim+CHANNEL_PACK-1)/CHANNEL_PACK;\n" " for (int i=0; i= 2\n" +" {\n" +" UCHAR4_TO_FLOAT8(charWeightsInt40.s4567,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)in.s1,wei,out0);\n" +" out1=mad((COMPUTE_FLOAT8)in.s5,wei,out1);\n" +" out2=mad((COMPUTE_FLOAT8)in.s9,wei,out2);\n" +" out3=mad((COMPUTE_FLOAT8)in.sd,wei,out3);\n" +" }\n" +" #endif\n" +" #if INPUT_CHANNEL_LEAVES_NUM >= 3\n" +" {\n" +" UCHAR4_TO_FLOAT8(charWeightsInt40.s89ab,scale,offset);\n" +" out0=mad((COMPUTE_FLOAT8)in.s2,wei,out0);\n" +" out1=mad((COMPUTE_FLOAT8)in.s6,wei,out1);\n" +" out2=mad((COMPUTE_FLOAT8)in.sa,wei,out2);\n" +" out3=mad((COMPUTE_FLOAT8)in.se,wei,out3);\n" " }\n" " #endif\n" +" }\n" " #endif\n" " }\n" +"#if INPUT_BATCH_LEAVES_NUM != 0\n" " }\n" +"#endif\n" " \n" "#ifdef RELU\n" -" out=fmax(out,(COMPUTE_FLOAT4)0);\n" -" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out0=fmax(out0,(COMPUTE_FLOAT8)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT8)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT8)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT8)0);\n" "#endif\n" "#ifdef RELU6\n" -" out=clamp(out,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" -" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" -"#endif\n" -" vstore4(CONVERT_FLOAT4(out),0,output+out_offset);\n" -" vstore4(CONVERT_FLOAT4(out1),0,output+out_offset+4);\n" -"}\n" -"__kernel void gemm_b4_c1_buf(GLOBAL_SIZE_DIM2\n" +" out0=clamp(out0,(COMPUTE_FLOAT8)0,(COMPUTE_FLOAT8)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT8)0,(COMPUTE_FLOAT8)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT8)0,(COMPUTE_FLOAT8)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT8)0,(COMPUTE_FLOAT8)6);\n" +"#endif\n" +" vstore4(CONVERT_FLOAT4(out0.s0123),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out0.s4567),0,output+out_offset+bhw4);\n" +" if(out_b_idx+1 >= bhw) return;\n" +" out_offset += 4;\n" +" vstore4(CONVERT_FLOAT4(out1.s0123),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1.s4567),0,output+out_offset+bhw4);\n" +" if(out_b_idx+2 >= bhw) return;\n" +" out_offset += 4;\n" +" vstore4(CONVERT_FLOAT4(out2.s0123),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2.s4567),0,output+out_offset+bhw4);\n" +" if(out_b_idx+3 >= bhw) return;\n" +" out_offset += 4;\n" +" vstore4(CONVERT_FLOAT4(out3.s0123),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3.s4567),0,output+out_offset+bhw4);\n" +"}\n" +"__kernel void gemm_b4_c8_int8_buf(GLOBAL_SIZE_DIM2\n" " __global const FLOAT* input,\n" "#ifdef USE_IMAGE\n" " __read_only image2d_t weight,\n" "#else\n" -"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" " __global const char *weight,\n" -"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" -" __global const uchar *weight,\n" -"#endif\n" "#endif\n" " __global const float *dequantScaleOffset,\n" " __global const FLOAT *bias,\n" " __global FLOAT* output,\n" -" __private const int bhw4,\n" +" __private const int bhw,\n" " __private const int dstChannelAlign,\n" " __private const int srcChannelAlign,\n" " __private const int blockNum,\n" " __private const int blockDim) {\n" -" const int x=get_global_id(0); //c\n" -" const int y=get_global_id(1); //b\n" +" const int x=get_global_id(0); //b/4\n" +" const int y=get_global_id(1); //c/8\n" " UNIFORM_BOUNDRY_CHECK(x,y);\n" -" const int out_c_idx=x;\n" -" const int out_b_idx=y << 2;\n" -" COMPUTE_FLOAT bias0=bias[out_c_idx];\n" -" COMPUTE_FLOAT4 out=(COMPUTE_FLOAT4)bias0;\n" " \n" -"#ifdef FORMAT_CNHW\n" -" int input_offset=out_b_idx*16;\n" -"#else\n" -" int input_offset=out_b_idx*srcChannelAlign;\n" -"#endif\n" -" int out_offset=out_b_idx*dstChannelAlign+out_c_idx*4;\n" +" const int out_b_idx=x << 2;\n" +" const int out_c_idx=y << 1;\n" +" COMPUTE_FLOAT8 out0=CONVERT_FLOAT8(vload8(0,bias+(out_c_idx << 2)));\n" +" COMPUTE_FLOAT8 out1=out0;\n" +" COMPUTE_FLOAT8 out2=out0;\n" +" COMPUTE_FLOAT8 out3=out0;\n" +" \n" +" const int bhw4=bhw << 2;\n" +" const int input_offset=out_b_idx*4;\n" +" int out_offset=out_c_idx*bhw4+out_b_idx*4;\n" "#ifndef USE_IMAGE\n" -" int weight_offset=out_c_idx*WEIGHT_STRIDE;\n" -" int weight_oc_offset=dstChannelAlign*WEIGHT_STRIDE;\n" +" const int weight_offset=y*srcChannelAlign*8;\n" "#endif\n" -" const int loop=(blockDim+CHANNEL_PACK-1)/CHANNEL_PACK;\n" -" \n" +" const int loop=(blockDim+4-1)/4;\n" +"#if INPUT_CHANNEL_LEAVES_NUM != 0\n" +" const int loop_end=max(loop-1,0);\n" +"#else\n" +" const int loop_end=loop;\n" +"#endif\n" +"#if INPUT_BATCH_LEAVES_NUM != 0\n" +" if(out_b_idx+3 >= bhw){\n" " for (int i=0; i= 2\n" +" COMPUTE_FLOAT4 in1=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+k*bhw4+4));\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" COMPUTE_FLOAT4 in2=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+k*bhw4+8));\n" +" #endif\n" +" {\n" +" out0=mad((COMPUTE_FLOAT8)in0.s0,wei0.s01234567,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s0,wei0.s01234567,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s0,wei0.s01234567,out2);\n" +" #endif\n" " }\n" -" #pragma unroll\n" -" for (int i=0; i<16; ++i){\n" -" COMPUTE_FLOAT4 in=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+(k32+i+16)*4));\n" -" out=mad(in,weights01_ptr[i],out);\n" +" {\n" +" out0=mad((COMPUTE_FLOAT8)in0.s1,wei0.s89abcdef,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s1,wei0.s89abcdef,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s1,wei0.s89abcdef,out2);\n" +" #endif\n" " }\n" +" {\n" +" out0=mad((COMPUTE_FLOAT8)in0.s2,wei1.s01234567,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s2,wei1.s01234567,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s2,wei1.s01234567,out2);\n" " #endif\n" +" }\n" +" {\n" +" out0=mad((COMPUTE_FLOAT8)in0.s3,wei1.s89abcdef,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s3,wei1.s89abcdef,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s3,wei1.s89abcdef,out2);\n" +" #endif\n" +" }\n" +" }\n" +" #if INPUT_CHANNEL_LEAVES_NUM != 0\n" +" {\n" +" int k=i*loop+loop_end;\n" +" int k2=k << 1;\n" +" COMPUTE_FLOAT4 in0=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+k*bhw4));\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" COMPUTE_FLOAT4 in1=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+k*bhw4+4));\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" COMPUTE_FLOAT4 in2=CONVERT_COMPUTE_FLOAT4(vload4(0,input+input_offset+k*bhw4+8));\n" +" #endif\n" +" #ifdef USE_IMAGE\n" +" COMPUTE_FLOAT16 wei0=CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight,SAMPLER,(int2)(k2,y))))*scale+offset;\n" +" COMPUTE_FLOAT16 wei1=CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight,SAMPLER,(int2)(k2+1,y))))*scale+offset;\n" " #else\n" -" COMPUTE_FLOAT16 weights;\n" +" COMPUTE_FLOAT16 wei0=CONVERT_COMPUTE_FLOAT16(vload16(k2,weight+weight_offset))*scale+offset;\n" +" COMPUTE_FLOAT16 wei1=CONVERT_COMPUTE_FLOAT16(vload16(k2+1,weight+weight_offset))*scale+offset;\n" +" #endif\n" +" {\n" +" out0=mad((COMPUTE_FLOAT8)in0.s0,wei0.s01234567,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s0,wei0.s01234567,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s0,wei0.s01234567,out2);\n" +" #endif\n" +" }\n" +" #if INPUT_CHANNEL_LEAVES_NUM >= 2\n" +" {\n" +" out0=mad((COMPUTE_FLOAT8)in0.s1,wei0.s89abcdef,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s1,wei0.s89abcdef,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s1,wei0.s89abcdef,out2);\n" +" #endif\n" +" }\n" +" #endif\n" +" #if INPUT_CHANNEL_LEAVES_NUM >= 3\n" +" {\n" +" out0=mad((COMPUTE_FLOAT8)in0.s2,wei1.s01234567,out0);\n" +" #if INPUT_BATCH_LEAVES_NUM >= 2\n" +" out1=mad((COMPUTE_FLOAT8)in1.s2,wei1.s01234567,out1);\n" +" #endif\n" +" #if INPUT_BATCH_LEAVES_NUM >= 3\n" +" out2=mad((COMPUTE_FLOAT8)in2.s2,wei1.s01234567,out2);\n" +" #endif\n" +" }\n" +" #endif\n" +" }\n" +" #endif\n" +" }\n" +" } else {\n" +"#endif\n" +" for (int i=0; i= 2\n" +" {\n" +" out0=mad((COMPUTE_FLOAT8)in.s1,wei0.s89abcdef,out0);\n" +" out1=mad((COMPUTE_FLOAT8)in.s5,wei0.s89abcdef,out1);\n" +" out2=mad((COMPUTE_FLOAT8)in.s9,wei0.s89abcdef,out2);\n" +" out3=mad((COMPUTE_FLOAT8)in.sd,wei0.s89abcdef,out3);\n" " }\n" " #endif\n" +" #if INPUT_CHANNEL_LEAVES_NUM >= 3\n" +" {\n" +" out0=mad((COMPUTE_FLOAT8)in.s2,wei1.s01234567,out0);\n" +" out1=mad((COMPUTE_FLOAT8)in.s6,wei1.s01234567,out1);\n" +" out2=mad((COMPUTE_FLOAT8)in.sa,wei1.s01234567,out2);\n" +" out3=mad((COMPUTE_FLOAT8)in.se,wei1.s01234567,out3);\n" +" }\n" +" #endif\n" +" }\n" " #endif\n" " }\n" +"#if INPUT_BATCH_LEAVES_NUM != 0\n" " }\n" +"#endif\n" " \n" "#ifdef RELU\n" -" out=fmax(out,(COMPUTE_FLOAT4)0);\n" +" out0=fmax(out0,(COMPUTE_FLOAT8)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT8)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT8)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT8)0);\n" "#endif\n" "#ifdef RELU6\n" -" out=clamp(out,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" -"#endif\n" -" vstore4(CONVERT_FLOAT4(out),0,output+out_offset);\n" +" out0=clamp(out0,(COMPUTE_FLOAT8)0,(COMPUTE_FLOAT8)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT8)0,(COMPUTE_FLOAT8)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT8)0,(COMPUTE_FLOAT8)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT8)0,(COMPUTE_FLOAT8)6);\n" +"#endif\n" +" vstore4(CONVERT_FLOAT4(out0.s0123),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out0.s4567),0,output+out_offset+bhw4);\n" +" if(out_b_idx+1 >= bhw) return;\n" +" out_offset += 4;\n" +" vstore4(CONVERT_FLOAT4(out1.s0123),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1.s4567),0,output+out_offset+bhw4);\n" +" if(out_b_idx+2 >= bhw) return;\n" +" out_offset += 4;\n" +" vstore4(CONVERT_FLOAT4(out2.s0123),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2.s4567),0,output+out_offset+bhw4);\n" +" if(out_b_idx+3 >= bhw) return;\n" +" out_offset += 4;\n" +" vstore4(CONVERT_FLOAT4(out3.s0123),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3.s4567),0,output+out_offset+bhw4);\n" "}\n" ; #endif diff --git a/source/backend/opencl/execution/cl/self_attention_buf.cl b/source/backend/opencl/execution/cl/self_attention_buf.cl index dc77548e1..963a50a3e 100644 --- a/source/backend/opencl/execution/cl/self_attention_buf.cl +++ b/source/backend/opencl/execution/cl/self_attention_buf.cl @@ -64,7 +64,6 @@ __kernel void split_transpose_qkv(GLOBAL_SIZE_3_DIMS const int b = z / head_num; const int hn = z % head_num; - const int seq_len_4 = (seq_len + 3) / 4; const int offset_q = ((b * head_num + hn) * head_dim_pack_k + 4 * hd) * seq_len_piece + 4 * sl; if(seq_index > 0) { diff --git a/source/backend/vulkan/component/VulkanInstance.hpp b/source/backend/vulkan/component/VulkanInstance.hpp index cc57d0c88..8a297ab6b 100644 --- a/source/backend/vulkan/component/VulkanInstance.hpp +++ b/source/backend/vulkan/component/VulkanInstance.hpp @@ -11,6 +11,8 @@ #include "core/NonCopyable.hpp" #include "backend/vulkan/vulkan/vulkan_wrapper.h" +#include + namespace MNN { class VulkanInstance : public NonCopyable { public: diff --git a/source/backend/vulkan/image/compiler/AllShader.cpp b/source/backend/vulkan/image/compiler/AllShader.cpp index fad0c7f55..6d70d11a2 100644 --- a/source/backend/vulkan/image/compiler/AllShader.cpp +++ b/source/backend/vulkan/image/compiler/AllShader.cpp @@ -375,97 +375,25 @@ unsigned int glsl_deconvCol2Im_comp_len = 2292; const unsigned char glsl_softmaxImage_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x77, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x7d, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x06, 0x00, 0x05, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x05, 0x00, 0x05, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 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0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x27, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, 0x08, 0x01, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, @@ -473,173 +401,47 @@ const unsigned char glsl_softmaxImage_comp[] = { 0x31, 0x00, 0x00, 0x00, 0x15, 0x00, 0x04, 0x00, 0x44, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x44, 0x00, 0x00, 0x00, 0x45, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x2b, 0x00, 0x04, 0x00, 0x44, 0x00, 0x00, 0x00, 0x47, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x19, 0x00, 0x00, 0x00, - 0x4b, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x2c, 0x00, 0x07, 0x00, - 0x1a, 0x00, 0x00, 0x00, 0x4c, 0x00, 0x00, 0x00, 0x4b, 0x00, 0x00, 0x00, - 0x4b, 0x00, 0x00, 0x00, 0x4b, 0x00, 0x00, 0x00, 0x4b, 0x00, 0x00, 0x00, - 0x19, 0x00, 0x09, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x19, 0x00, 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0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -650,33 +452,7 @@ const unsigned char glsl_softmaxImage_AXIS_N_comp[] = { 0x11, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xc2, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, - 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x0a, 0x00, - 0x08, 0x00, 0x00, 0x00, 0x63, 0x61, 0x6c, 0x63, 0x75, 0x6c, 0x61, 0x74, - 0x65, 0x4e, 0x75, 0x6d, 0x45, 0x6c, 0x65, 0x50, 0x65, 0x72, 0x49, 0x6e, - 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x28, 0x00, 0x00, 0x00, - 0x05, 0x00, 0x0a, 0x00, 0x14, 0x00, 0x00, 0x00, 0x63, 0x61, 0x6c, 0x63, - 0x75, 0x6c, 0x61, 0x74, 0x65, 0x50, 0x6f, 0x73, 0x28, 0x75, 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0x13, 0x00, 0x02, 0x00, 0x02, 0x00, 0x00, 0x00, 0x21, 0x00, 0x03, 0x00, + 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x15, 0x00, 0x04, 0x00, + 0x06, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x15, 0x00, 0x04, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x0c, 0x00, 0x00, 0x00, - 0x0b, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x21, 0x00, 0x09, 0x00, - 0x0d, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, - 0x0a, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, - 0x0a, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x16, 0x00, 0x03, 0x00, + 0x0b, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x16, 0x00, 0x03, 0x00, 0x16, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x17, 0x00, 0x00, 0x00, 0x16, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, - 0x20, 0x00, 0x04, 0x00, 0x18, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, - 0x17, 0x00, 0x00, 0x00, 0x21, 0x00, 0x05, 0x00, 0x19, 0x00, 0x00, 0x00, - 0x17, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x23, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x1e, 0x00, 0x07, 0x00, 0x24, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, @@ -817,641 +521,349 @@ const unsigned char glsl_softmaxImage_AXIS_N_comp[] = { 0x47, 0x00, 0x00, 0x00, 0x14, 0x00, 0x02, 0x00, 0x4a, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x16, 0x00, 0x00, 0x00, 0x4c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x3f, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, - 0x4e, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, - 0x4f, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x16, 0x00, 0x00, 0x00, - 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x52, 0x00, 0x00, 0x00, - 0x02, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x16, 0x00, 0x00, 0x00, - 0x5b, 0x00, 0x00, 0x00, 0xff, 0xff, 0x7f, 0xff, 0x2c, 0x00, 0x07, 0x00, - 0x17, 0x00, 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0x01, 0x00, 0x00, + 0x7e, 0x01, 0x00, 0x00, 0x80, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x86, 0x01, 0x00, 0x00, 0x01, 0x02, 0x00, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0xf9, 0x00, 0x02, 0x00, 0x5a, 0x01, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x5c, 0x01, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_softmaxImage_AXIS_H_comp_len = 9688; +unsigned int glsl_softmaxImage_AXIS_H_comp_len = 4908; const unsigned char glsl_softmaxImage_AXIS_W_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x88, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x12, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -2274,33 +1287,7 @@ const unsigned char glsl_softmaxImage_AXIS_W_comp[] = { 0x11, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xc2, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, - 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x0a, 0x00, - 0x08, 0x00, 0x00, 0x00, 0x63, 0x61, 0x6c, 0x63, 0x75, 0x6c, 0x61, 0x74, - 0x65, 0x4e, 0x75, 0x6d, 0x45, 0x6c, 0x65, 0x50, 0x65, 0x72, 0x49, 0x6e, - 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x28, 0x00, 0x00, 0x00, - 0x05, 0x00, 0x0a, 0x00, 0x14, 0x00, 0x00, 0x00, 0x63, 0x61, 0x6c, 0x63, - 0x75, 0x6c, 0x61, 0x74, 0x65, 0x50, 0x6f, 0x73, 0x28, 0x75, 0x31, 0x3b, - 0x75, 0x31, 0x3b, 0x75, 0x31, 0x3b, 0x75, 0x31, 0x3b, 0x75, 0x31, 0x3b, - 0x75, 0x31, 0x3b, 0x00, 0x05, 0x00, 0x04, 0x00, 0x0e, 0x00, 0x00, 0x00, - 0x69, 0x6e, 0x64, 0x65, 0x78, 0x4e, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, - 0x0f, 0x00, 0x00, 0x00, 0x69, 0x6e, 0x64, 0x65, 0x78, 0x48, 0x00, 0x00, - 0x05, 0x00, 0x04, 0x00, 0x10, 0x00, 0x00, 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0x00, + 0x7e, 0x01, 0x00, 0x00, 0x80, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x86, 0x01, 0x00, 0x00, 0x01, 0x02, 0x00, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0xf9, 0x00, 0x02, 0x00, 0x5a, 0x01, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x5c, 0x01, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_softmaxImage_AXIS_W_comp_len = 9688; +unsigned int glsl_softmaxImage_AXIS_W_comp_len = 4908; const unsigned char glsl_softmaxImage_AXIS_C_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xa2, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x37, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -3086,33 +1700,7 @@ const unsigned char glsl_softmaxImage_AXIS_C_comp[] = { 0x11, 0x00, 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0x00, 0x00, 0x00, 0x7e, 0x00, 0x00, 0x00, 0x7d, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x7f, 0x00, 0x00, 0x00, 0x7e, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, @@ -3378,265 +1824,182 @@ const unsigned char glsl_softmaxImage_AXIS_C_comp[] = { 0x80, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x82, 0x00, 0x00, 0x00, 0x81, 0x00, 0x00, 0x00, 0x89, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0x83, 0x00, 0x00, 0x00, 0x7f, 0x00, 0x00, 0x00, - 0x82, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x7c, 0x00, 0x00, 0x00, - 0x83, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x79, 0x00, 0x00, 0x00, - 0x85, 0x00, 0x00, 0x00, 0x7d, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x86, 0x00, 0x00, 0x00, - 0x85, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x28, 0x00, 0x00, 0x00, - 0x87, 0x00, 0x00, 0x00, 0x26, 0x00, 0x00, 0x00, 0x80, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 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const unsigned char glsl_softmaxImage_AXIS_C_comp[] = { 0xf7, 0x00, 0x03, 0x00, 0x3e, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x3c, 0x01, 0x00, 0x00, 0x3d, 0x01, 0x00, 0x00, 0x3e, 0x01, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x3d, 0x01, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x17, 0x00, 0x00, 0x00, 0x40, 0x01, 0x00, 0x00, - 0x2b, 0x01, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x3f, 0x01, 0x00, 0x00, - 0x40, 0x01, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x28, 0x00, 0x00, 0x00, - 0x42, 0x01, 0x00, 0x00, 0x26, 0x00, 0x00, 0x00, 0xc5, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x43, 0x01, 0x00, 0x00, - 0x42, 0x01, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x41, 0x01, 0x00, 0x00, - 0x43, 0x01, 0x00, 0x00, 0x39, 0x00, 0x06, 0x00, 0x17, 0x00, 0x00, 0x00, - 0x44, 0x01, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x3f, 0x01, 0x00, 0x00, - 0x41, 0x01, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x2b, 0x01, 0x00, 0x00, - 0x44, 0x01, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x3e, 0x01, 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0x01, 0x00, 0x00, 0x94, 0x01, 0x00, 0x00, + 0x97, 0x01, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x99, 0x01, 0x00, 0x00, + 0x9c, 0x01, 0x00, 0x00, 0x9b, 0x01, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, + 0x9c, 0x01, 0x00, 0x00, 0x07, 0x02, 0x00, 0x00, 0x98, 0x01, 0x00, 0x00, + 0x80, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0xa0, 0x01, 0x00, 0x00, + 0x26, 0x02, 0x00, 0x00, 0x2b, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, + 0x70, 0x01, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x72, 0x01, 0x00, 0x00, + 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_softmaxImage_AXIS_C_comp_len = 10308; +unsigned int glsl_softmaxImage_AXIS_C_comp_len = 5204; const unsigned char glsl_convolutionDepthwiseMali_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xec, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xdb, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 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0x00, 0x00, 0x00, + 0x2a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x3d, 0x00, 0x04, 0x00, 0x07, 0x00, 0x00, 0x00, 0x2c, 0x00, 0x00, 0x00, + 0x10, 0x00, 0x00, 0x00, 0x4f, 0x00, 0x07, 0x00, 0x11, 0x00, 0x00, 0x00, + 0x2d, 0x00, 0x00, 0x00, 0x2c, 0x00, 0x00, 0x00, 0x2c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0xb1, 0x00, 0x05, 0x00, 0x2f, 0x00, 0x00, 0x00, 0x30, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, 0x9b, 0x00, 0x04, 0x00, 0x2e, 0x00, 0x00, 0x00, @@ -4091,169 +2337,240 @@ const unsigned char glsl_convolutionDepthwiseMali_comp[] = { 0x33, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x31, 0x00, 0x00, 0x00, 0x32, 0x00, 0x00, 0x00, 0x33, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x32, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, - 0x3e, 0x00, 0x00, 0x00, 0x3f, 0x00, 0x00, 0x00, 0x15, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x11, 0x00, 0x00, 0x00, - 0x40, 0x00, 0x00, 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-unsigned int glsl_convolutionDepthwiseMali_RELU_comp_len = 3796; +unsigned int glsl_convolutionDepthwiseMali_RELU_comp_len = 5360; const unsigned char glsl_convolutionDepthwiseMali_RELU6_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xf2, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xe1, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -4585,317 +3032,447 @@ const unsigned char glsl_convolutionDepthwiseMali_RELU6_comp[] = { 0x08, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, 0x0d, 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+8329,7 @@ unsigned int glsl_unaryImage_GELU_comp_len = 2272; const unsigned char glsl_unaryImage_SILU_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x56, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x4d, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -9763,57 +8340,66 @@ const unsigned char glsl_unaryImage_SILU_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, 0x0d, 0x00, 0x00, 0x00, - 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, 0x6c, 0x49, 0x6e, 0x76, - 0x6f, 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0x00, 0x00, 0x00, 0x1a, 0x00, 0x00, 0x00, @@ -9847,38 +8437,62 @@ const unsigned char glsl_unaryImage_SILU_comp[] = { 0x13, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0x1f, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x1d, 0x00, 0x00, 0x00, 0x1e, 0x00, 0x00, 0x00, 0x1f, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x1e, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x1e, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, + 0x11, 0x00, 0x00, 0x00, 0x23, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, + 0x10, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x24, 0x00, 0x00, 0x00, 0x23, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, 0x19, 0x00, 0x00, 0x00, 0x26, 0x00, 0x00, 0x00, 0x17, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x25, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x27, 0x00, 0x00, 0x00, 0x26, 0x00, 0x00, 0x00, 0x8b, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, - 0x13, 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0x00, 0x00, + 0x03, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x71, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, @@ -10013,363 +8591,202 @@ const unsigned char glsl_im2col_comp[] = { 0xe0, 0x00, 0x00, 0x00, 0x4f, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x16, 0x00, 0x03, 0x00, 0x03, 0x01, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x04, 0x01, 0x00, 0x00, 0x03, 0x01, 0x00, 0x00, - 0x04, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x05, 0x01, 0x00, 0x00, - 0x07, 0x00, 0x00, 0x00, 0x04, 0x01, 0x00, 0x00, 0x19, 0x00, 0x09, 0x00, - 0x07, 0x01, 0x00, 0x00, 0x03, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x03, 0x00, - 0x08, 0x01, 0x00, 0x00, 0x07, 0x01, 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0x00, + 0xdc, 0x00, 0x00, 0x00, 0xb1, 0x00, 0x05, 0x00, 0xe0, 0x00, 0x00, 0x00, + 0xe1, 0x00, 0x00, 0x00, 0xcd, 0x00, 0x00, 0x00, 0x96, 0x00, 0x00, 0x00, + 0x9b, 0x00, 0x04, 0x00, 0x4f, 0x00, 0x00, 0x00, 0xe2, 0x00, 0x00, 0x00, + 0xe1, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0xe4, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0xe2, 0x00, 0x00, 0x00, + 0xe3, 0x00, 0x00, 0x00, 0xe4, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0xe3, 0x00, 0x00, 0x00, 0xaf, 0x00, 0x05, 0x00, 0xe0, 0x00, 0x00, 0x00, + 0xe7, 0x00, 0x00, 0x00, 0xcd, 0x00, 0x00, 0x00, 0x86, 0x00, 0x00, 0x00, 0x9b, 0x00, 0x04, 0x00, 0x4f, 0x00, 0x00, 0x00, 0xe8, 0x00, 0x00, 0x00, 0xe7, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0xe4, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0xe4, 0x00, 0x00, 0x00, 0xf5, 0x00, 0x07, 0x00, @@ -10378,115 +8795,74 @@ const unsigned char glsl_im2col_comp[] = { 0xf7, 0x00, 0x03, 0x00, 0xeb, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0xe9, 0x00, 0x00, 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0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -10497,141 +8873,198 @@ const unsigned char glsl_convolutionDepthwise_comp[] = { 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, 0x0d, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x03, 0x00, 0x09, 0x00, 0x00, 0x00, + 0x70, 0x6f, 0x73, 0x00, 0x05, 0x00, 0x08, 0x00, 0x0d, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, 0x44, 0x00, 0x00, 0x00, - 0x05, 0x00, 0x05, 0x00, 0x13, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6e, 0x73, - 0x74, 0x42, 0x75, 0x66, 0x66, 0x65, 0x72, 0x00, 0x06, 0x00, 0x04, 0x00, - 0x13, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x70, 0x61, 0x64, 0x00, - 0x06, 0x00, 0x06, 0x00, 0x13, 0x00, 0x00, 0x00, 0x01, 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0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -10812,317 +9316,447 @@ const unsigned char glsl_convolutionDepthwise_RELU_comp[] = { 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, 0x0d, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x03, 0x00, 0x09, 0x00, 0x00, 0x00, + 0x70, 0x6f, 0x73, 0x00, 0x05, 0x00, 0x08, 0x00, 0x0d, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, 0x44, 0x00, 0x00, 0x00, - 0x05, 0x00, 0x05, 0x00, 0x13, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6e, 0x73, - 0x74, 0x42, 0x75, 0x66, 0x66, 0x65, 0x72, 0x00, 0x06, 0x00, 0x04, 0x00, - 0x13, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x70, 0x61, 0x64, 0x00, - 0x06, 0x00, 0x06, 0x00, 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0x00, 0x02, 0x00, + 0x33, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x33, 0x00, 0x00, 0x00, + 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_convolutionDepthwise_RELU6_comp_len = 3844; +unsigned int glsl_convolutionDepthwise_RELU6_comp_len = 5408; const unsigned char glsl_gridSampleBilinear_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -11757,7 +10521,7 @@ unsigned int glsl_gridSampleBilinear_comp_len = 3672; const unsigned char glsl_gridSampleBilinear_PAD_MODE_ZEROS_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x56, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xfe, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -11768,108 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int glsl_gridSampleBilinear_PAD_MODE_ZEROS_comp_len = 8448; +unsigned int glsl_gridSampleBilinear_PAD_MODE_ZEROS_comp_len = 4524; const unsigned char glsl_gridSampleNearest_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -12715,7 +11152,7 @@ unsigned int glsl_gridSampleNearest_comp_len = 2952; const unsigned char glsl_gridSampleNearest_PAD_MODE_ZEROS_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xde, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xf5, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -12726,12 +11163,9 @@ const unsigned char glsl_gridSampleNearest_PAD_MODE_ZEROS_comp[] = { 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 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glsl_gridSampleNearest_PAD_MODE_ZEROS_comp_len = 3264; const unsigned char glsl_relu6_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -13460,7 +11735,7 @@ unsigned int glsl_binaryImage_comp_len = 1936; const unsigned char glsl_binaryImage_ADD_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x79, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x89, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -13471,29 +11746,22 @@ const unsigned char glsl_binaryImage_ADD_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 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0x14, 0x00, 0x00, 0x00, 0x67, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x69, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, @@ -13699,26 +11915,24 @@ const unsigned char glsl_binaryImage_ADD_comp[] = { 0x69, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0x6c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x6a, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x6c, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, - 0x37, 0x00, 0x00, 0x00, 0x6d, 0x00, 0x00, 0x00, 0x62, 0x00, 0x00, 0x00, - 0x0c, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, 0x6d, 0x00, 0x00, 0x00, - 0x6f, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x62, 0x00, 0x00, 0x00, - 0x70, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x07, 0x00, + 0x37, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x28, 0x00, 0x00, 0x00, 0x66, 0x00, 0x00, 0x00, 0x6f, 0x00, 0x00, 0x00, + 0xf9, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x6c, 0x00, 0x00, 0x00, 0xf5, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, + 0x88, 0x00, 0x00, 0x00, 0x66, 0x00, 0x00, 0x00, 0x5e, 0x00, 0x00, 0x00, + 0x70, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x71, 0x00, 0x00, 0x00, 0x74, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x26, 0x00, 0x00, 0x00, 0x75, 0x00, 0x00, 0x00, - 0x28, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x37, 0x00, 0x00, 0x00, - 0x76, 0x00, 0x00, 0x00, 0x62, 0x00, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, - 0x74, 0x00, 0x00, 0x00, 0x75, 0x00, 0x00, 0x00, 0x76, 0x00, 0x00, 0x00, - 0xf9, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x25, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 + 0x63, 0x00, 0x04, 0x00, 0x74, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, + 0x88, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, + 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_binaryImage_ADD_comp_len = 3048; +unsigned int glsl_binaryImage_ADD_comp_len = 2308; const unsigned char glsl_binaryImage_SUB_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x79, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x89, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -13729,29 +11943,22 @@ const unsigned char glsl_binaryImage_SUB_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 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0x00, 0x04, 0x00, 0x37, 0x00, 0x00, 0x00, 0x65, 0x00, 0x00, 0x00, - 0x50, 0x00, 0x00, 0x00, 0x83, 0x00, 0x05, 0x00, 0x37, 0x00, 0x00, 0x00, - 0x66, 0x00, 0x00, 0x00, 0x64, 0x00, 0x00, 0x00, 0x65, 0x00, 0x00, 0x00, - 0x3e, 0x00, 0x03, 0x00, 0x62, 0x00, 0x00, 0x00, 0x66, 0x00, 0x00, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x5d, 0x00, 0x00, 0x00, 0x51, 0x00, 0x05, 0x00, + 0x36, 0x00, 0x00, 0x00, 0x60, 0x00, 0x00, 0x00, 0x59, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x50, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, + 0x61, 0x00, 0x00, 0x00, 0x60, 0x00, 0x00, 0x00, 0x60, 0x00, 0x00, 0x00, + 0x60, 0x00, 0x00, 0x00, 0x60, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, + 0x5e, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x5e, 0x00, 0x00, 0x00, + 0xf5, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, 0x87, 0x00, 0x00, 0x00, + 0x59, 0x00, 0x00, 0x00, 0x4b, 0x00, 0x00, 0x00, 0x61, 0x00, 0x00, 0x00, + 0x5d, 0x00, 0x00, 0x00, 0x83, 0x00, 0x05, 0x00, 0x37, 0x00, 0x00, 0x00, + 0x66, 0x00, 0x00, 0x00, 0x86, 0x00, 0x00, 0x00, 0x87, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x1f, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x67, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x69, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, @@ -13957,26 +12112,24 @@ const unsigned char glsl_binaryImage_SUB_comp[] = { 0x69, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0x6c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x6a, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x6c, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, - 0x37, 0x00, 0x00, 0x00, 0x6d, 0x00, 0x00, 0x00, 0x62, 0x00, 0x00, 0x00, - 0x0c, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, 0x6d, 0x00, 0x00, 0x00, - 0x6f, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x62, 0x00, 0x00, 0x00, - 0x70, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x07, 0x00, + 0x37, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x28, 0x00, 0x00, 0x00, 0x66, 0x00, 0x00, 0x00, 0x6f, 0x00, 0x00, 0x00, + 0xf9, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x6c, 0x00, 0x00, 0x00, 0xf5, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, + 0x88, 0x00, 0x00, 0x00, 0x66, 0x00, 0x00, 0x00, 0x5e, 0x00, 0x00, 0x00, + 0x70, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x71, 0x00, 0x00, 0x00, 0x74, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x26, 0x00, 0x00, 0x00, 0x75, 0x00, 0x00, 0x00, - 0x28, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x37, 0x00, 0x00, 0x00, - 0x76, 0x00, 0x00, 0x00, 0x62, 0x00, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, - 0x74, 0x00, 0x00, 0x00, 0x75, 0x00, 0x00, 0x00, 0x76, 0x00, 0x00, 0x00, - 0xf9, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x25, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 + 0x63, 0x00, 0x04, 0x00, 0x74, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, + 0x88, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, + 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_binaryImage_SUB_comp_len = 3048; +unsigned int glsl_binaryImage_SUB_comp_len = 2308; const unsigned char glsl_binaryImage_MUL_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x79, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x89, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -13987,29 +12140,22 @@ const unsigned char glsl_binaryImage_MUL_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x09, 0x00, 0x00, 0x00, - 0x70, 0x6f, 0x73, 0x54, 0x6d, 0x70, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0d, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, - 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, - 0x44, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x10, 0x00, 0x00, 0x00, - 0x69, 0x6e, 0x53, 0x69, 0x7a, 0x65, 0x00, 0x00, 0x05, 0x00, 0x05, 0x00, - 0x12, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6e, 0x73, 0x74, 0x42, 0x75, 0x66, - 0x66, 0x65, 0x72, 0x00, 0x06, 0x00, 0x06, 0x00, 0x12, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x73, 0x74, 0x72, 0x69, 0x64, 0x65, 0x30, 0x30, - 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x06, 0x00, 0x12, 0x00, 0x00, 0x00, - 0x01, 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0x00, 0x0d, 0x00, 0x00, 0x00, + 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, 0x6c, 0x49, 0x6e, 0x76, + 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, 0x44, 0x00, 0x00, 0x00, + 0x05, 0x00, 0x05, 0x00, 0x12, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6e, 0x73, + 0x74, 0x42, 0x75, 0x66, 0x66, 0x65, 0x72, 0x00, 0x06, 0x00, 0x06, 0x00, + 0x12, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x73, 0x74, 0x72, 0x69, + 0x64, 0x65, 0x30, 0x30, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x06, 0x00, + 0x12, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x70, 0x6f, 0x73, 0x4c, + 0x69, 0x6d, 0x69, 0x74, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x07, 0x00, + 0x12, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x61, 0x63, 0x74, 0x69, + 0x76, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x54, 0x79, 0x70, 0x65, 0x00, 0x00, + 0x05, 0x00, 0x05, 0x00, 0x14, 0x00, 0x00, 0x00, 0x75, 0x43, 0x6f, 0x6e, + 0x73, 0x74, 0x61, 0x6e, 0x74, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, + 0x3d, 0x00, 0x00, 0x00, 0x75, 0x49, 0x6e, 0x70, 0x75, 0x74, 0x30, 0x00, + 0x05, 0x00, 0x04, 0x00, 0x51, 0x00, 0x00, 0x00, 0x75, 0x49, 0x6e, 0x70, + 0x75, 0x74, 0x31, 0x00, 0x05, 0x00, 0x04, 0x00, 0x73, 0x00, 0x00, 0x00, 0x75, 0x4f, 0x75, 0x74, 0x70, 0x75, 0x74, 0x00, 0x47, 0x00, 0x04, 0x00, 0x0d, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x48, 0x00, 0x05, 0x00, 0x12, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -14035,179 +12181,127 @@ const unsigned char glsl_binaryImage_MUL_comp[] = { 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x15, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x07, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, - 0x03, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, - 0x07, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x15, 0x00, 0x04, 0x00, - 0x0a, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x17, 0x00, 0x04, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, - 0x03, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 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0x5e, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x5e, 0x00, 0x00, 0x00, + 0xf5, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, 0x87, 0x00, 0x00, 0x00, + 0x59, 0x00, 0x00, 0x00, 0x4b, 0x00, 0x00, 0x00, 0x61, 0x00, 0x00, 0x00, + 0x5d, 0x00, 0x00, 0x00, 0x85, 0x00, 0x05, 0x00, 0x37, 0x00, 0x00, 0x00, + 0x66, 0x00, 0x00, 0x00, 0x86, 0x00, 0x00, 0x00, 0x87, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x1f, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x67, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x69, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, @@ -14215,26 +12309,24 @@ const unsigned char glsl_binaryImage_MUL_comp[] = { 0x69, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0x6c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x6a, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x6c, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, - 0x37, 0x00, 0x00, 0x00, 0x6d, 0x00, 0x00, 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0x00, 0x04, 0x00, 0x26, 0x00, 0x00, 0x00, 0x75, 0x00, 0x00, 0x00, - 0x28, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x37, 0x00, 0x00, 0x00, - 0x76, 0x00, 0x00, 0x00, 0x62, 0x00, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, - 0x74, 0x00, 0x00, 0x00, 0x75, 0x00, 0x00, 0x00, 0x76, 0x00, 0x00, 0x00, - 0xf9, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x25, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 + 0x63, 0x00, 0x04, 0x00, 0x74, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, + 0x88, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, + 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_binaryImage_MUL_comp_len = 3048; +unsigned int glsl_binaryImage_MUL_comp_len = 2308; const unsigned char glsl_binaryImage_DIV_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x80, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x91, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -14245,29 +12337,22 @@ const unsigned char glsl_binaryImage_DIV_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x09, 0x00, 0x00, 0x00, - 0x70, 0x6f, 0x73, 0x54, 0x6d, 0x70, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0d, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, - 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, - 0x44, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x10, 0x00, 0x00, 0x00, - 0x69, 0x6e, 0x53, 0x69, 0x7a, 0x65, 0x00, 0x00, 0x05, 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0x6d, 0x00, 0x00, 0x00, 0x5e, 0x00, 0x00, 0x00, 0x77, 0x00, 0x00, 0x00, + 0x72, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x78, 0x00, 0x00, 0x00, + 0x7b, 0x00, 0x00, 0x00, 0x7a, 0x00, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, + 0x7b, 0x00, 0x00, 0x00, 0x8b, 0x00, 0x00, 0x00, 0x90, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_binaryImage_DIV_comp_len = 3204; +unsigned int glsl_binaryImage_DIV_comp_len = 2448; const unsigned char glsl_binaryImage_POW_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x79, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x89, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -14516,29 +12545,22 @@ const unsigned char glsl_binaryImage_POW_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x09, 0x00, 0x00, 0x00, - 0x70, 0x6f, 0x73, 0x54, 0x6d, 0x70, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0d, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, - 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, - 0x44, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x10, 0x00, 0x00, 0x00, - 0x69, 0x6e, 0x53, 0x69, 0x7a, 0x65, 0x00, 0x00, 0x05, 0x00, 0x05, 0x00, - 0x12, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6e, 0x73, 0x74, 0x42, 0x75, 0x66, - 0x66, 0x65, 0x72, 0x00, 0x06, 0x00, 0x06, 0x00, 0x12, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x73, 0x74, 0x72, 0x69, 0x64, 0x65, 0x30, 0x30, - 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0x00, 0x66, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x1a, 0x00, 0x00, 0x00, - 0x64, 0x00, 0x00, 0x00, 0x65, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, - 0x62, 0x00, 0x00, 0x00, 0x66, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, + 0x86, 0x00, 0x00, 0x00, 0x87, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x1f, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x67, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x69, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, 0xaa, 0x00, 0x05, 0x00, @@ -14745,26 +12715,23 @@ const unsigned char glsl_binaryImage_POW_comp[] = { 0x40, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0x6c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x6a, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x37, 0x00, 0x00, 0x00, - 0x6d, 0x00, 0x00, 0x00, 0x62, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x07, 0x00, - 0x37, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x28, 0x00, 0x00, 0x00, 0x6d, 0x00, 0x00, 0x00, 0x6f, 0x00, 0x00, 0x00, - 0x3e, 0x00, 0x03, 0x00, 0x62, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, - 0xf9, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x6c, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x71, 0x00, 0x00, 0x00, - 0x74, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, - 0x26, 0x00, 0x00, 0x00, 0x75, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x37, 0x00, 0x00, 0x00, 0x76, 0x00, 0x00, 0x00, - 0x62, 0x00, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, 0x74, 0x00, 0x00, 0x00, - 0x75, 0x00, 0x00, 0x00, 0x76, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, - 0x25, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, - 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 + 0x6b, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, + 0x70, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, + 0x66, 0x00, 0x00, 0x00, 0x6f, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, + 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, + 0xf5, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, + 0x66, 0x00, 0x00, 0x00, 0x5e, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, + 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x71, 0x00, 0x00, 0x00, + 0x74, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, + 0x74, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, + 0xf9, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x25, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_binaryImage_POW_comp_len = 3056; +unsigned int glsl_binaryImage_POW_comp_len = 2316; const unsigned char glsl_binaryImage_VMAX_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x79, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x89, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -14775,29 +12742,22 @@ const unsigned char glsl_binaryImage_VMAX_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x09, 0x00, 0x00, 0x00, - 0x70, 0x6f, 0x73, 0x54, 0x6d, 0x70, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0d, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, - 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, - 0x44, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x10, 0x00, 0x00, 0x00, - 0x69, 0x6e, 0x53, 0x69, 0x7a, 0x65, 0x00, 0x00, 0x05, 0x00, 0x05, 0x00, - 0x12, 0x00, 0x00, 0x00, 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0x00, 0x3e, 0x00, 0x03, 0x00, - 0x62, 0x00, 0x00, 0x00, 0x66, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, + 0x86, 0x00, 0x00, 0x00, 0x87, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x1f, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x67, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x69, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, 0xaa, 0x00, 0x05, 0x00, @@ -15004,26 +12912,23 @@ const unsigned char glsl_binaryImage_VMAX_comp[] = { 0x40, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0x6c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x6a, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x37, 0x00, 0x00, 0x00, - 0x6d, 0x00, 0x00, 0x00, 0x62, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x07, 0x00, - 0x37, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x28, 0x00, 0x00, 0x00, 0x6d, 0x00, 0x00, 0x00, 0x6f, 0x00, 0x00, 0x00, - 0x3e, 0x00, 0x03, 0x00, 0x62, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, - 0xf9, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x6c, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x71, 0x00, 0x00, 0x00, - 0x74, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, - 0x26, 0x00, 0x00, 0x00, 0x75, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x37, 0x00, 0x00, 0x00, 0x76, 0x00, 0x00, 0x00, - 0x62, 0x00, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, 0x74, 0x00, 0x00, 0x00, - 0x75, 0x00, 0x00, 0x00, 0x76, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, - 0x25, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, - 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 + 0x6b, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, + 0x70, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, + 0x66, 0x00, 0x00, 0x00, 0x6f, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, + 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, + 0xf5, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, + 0x66, 0x00, 0x00, 0x00, 0x5e, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, + 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x71, 0x00, 0x00, 0x00, + 0x74, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, + 0x74, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, + 0xf9, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x25, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_binaryImage_VMAX_comp_len = 3056; +unsigned int glsl_binaryImage_VMAX_comp_len = 2316; const unsigned char glsl_binaryImage_SQUDIFF_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x7d, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x8d, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -15034,29 +12939,22 @@ const unsigned char glsl_binaryImage_SQUDIFF_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x09, 0x00, 0x00, 0x00, - 0x70, 0x6f, 0x73, 0x54, 0x6d, 0x70, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0d, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, - 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, - 0x44, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x10, 0x00, 0x00, 0x00, - 0x69, 0x6e, 0x53, 0x69, 0x7a, 0x65, 0x00, 0x00, 0x05, 0x00, 0x05, 0x00, - 0x12, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6e, 0x73, 0x74, 0x42, 0x75, 0x66, - 0x66, 0x65, 0x72, 0x00, 0x06, 0x00, 0x06, 0x00, 0x12, 0x00, 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0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -15298,29 +13137,22 @@ const unsigned char glsl_binaryImage_VMIN_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x09, 0x00, 0x00, 0x00, - 0x70, 0x6f, 0x73, 0x54, 0x6d, 0x70, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0d, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, - 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, - 0x44, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x10, 0x00, 0x00, 0x00, - 0x69, 0x6e, 0x53, 0x69, 0x7a, 0x65, 0x00, 0x00, 0x05, 0x00, 0x05, 0x00, - 0x12, 0x00, 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0xaa, 0x00, 0x05, 0x00, @@ -15527,22 +13307,19 @@ const unsigned char glsl_binaryImage_VMIN_comp[] = { 0x40, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0x6c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x6a, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x37, 0x00, 0x00, 0x00, - 0x6d, 0x00, 0x00, 0x00, 0x62, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x07, 0x00, - 0x37, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x28, 0x00, 0x00, 0x00, 0x6d, 0x00, 0x00, 0x00, 0x6f, 0x00, 0x00, 0x00, - 0x3e, 0x00, 0x03, 0x00, 0x62, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, - 0xf9, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x6c, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x71, 0x00, 0x00, 0x00, - 0x74, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, - 0x26, 0x00, 0x00, 0x00, 0x75, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x37, 0x00, 0x00, 0x00, 0x76, 0x00, 0x00, 0x00, - 0x62, 0x00, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, 0x74, 0x00, 0x00, 0x00, - 0x75, 0x00, 0x00, 0x00, 0x76, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, - 0x25, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, - 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 + 0x6b, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, + 0x70, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, + 0x66, 0x00, 0x00, 0x00, 0x6f, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, + 0x6c, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x6c, 0x00, 0x00, 0x00, + 0xf5, 0x00, 0x07, 0x00, 0x37, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, + 0x66, 0x00, 0x00, 0x00, 0x5e, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, + 0x6b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x71, 0x00, 0x00, 0x00, + 0x74, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, 0x63, 0x00, 0x04, 0x00, + 0x74, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, + 0xf9, 0x00, 0x02, 0x00, 0x25, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x25, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_binaryImage_VMIN_comp_len = 3056; +unsigned int glsl_binaryImage_VMIN_comp_len = 2316; const unsigned char glsl_matmul_input_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -15773,7 +13550,7 @@ unsigned int glsl_matmul_input_comp_len = 2672; const unsigned char glsl_matmul_input_TRANSPOSE_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xd3, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xfb, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -15784,54 +13561,41 @@ const unsigned char glsl_matmul_input_TRANSPOSE_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, - 0x70, 0x6f, 0x73, 0x58, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0c, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, - 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, - 0x44, 0x00, 0x00, 0x00, 0x05, 0x00, 0x06, 0x00, 0x17, 0x00, 0x00, 0x00, - 0x6f, 0x66, 0x66, 0x73, 0x65, 0x74, 0x42, 0x75, 0x66, 0x66, 0x65, 0x72, - 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x05, 0x00, 0x17, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x73, 0x69, 0x7a, 0x65, 0x00, 0x00, 0x00, 0x00, - 0x06, 0x00, 0x06, 0x00, 0x17, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x74, 0x72, 0x61, 0x6e, 0x73, 0x66, 0x6f, 0x72, 0x6d, 0x00, 0x00, 0x00, - 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0x04, 0x00, 0xd2, 0x00, 0x00, 0x00, + 0x0b, 0x00, 0x00, 0x00, 0x19, 0x00, 0x00, 0x00, 0x13, 0x00, 0x02, 0x00, + 0x02, 0x00, 0x00, 0x00, 0x21, 0x00, 0x03, 0x00, 0x03, 0x00, 0x00, 0x00, + 0x02, 0x00, 0x00, 0x00, 0x15, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x20, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x15, 0x00, 0x04, 0x00, 0x09, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x0b, 0x00, 0x00, 0x00, @@ -15854,107 +13618,67 @@ const unsigned char glsl_matmul_input_TRANSPOSE_comp[] = { 0x03, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x02, 0x00, 0x1f, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x23, 0x00, 0x00, 0x00, - 0x06, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, - 0x24, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x23, 0x00, 0x00, 0x00, - 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0x00, + 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_matmul_input_TRANSPOSE_comp_len = 4788; +unsigned int glsl_matmul_input_TRANSPOSE_comp_len = 3104; const unsigned char glsl_nchwToimage_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -16702,7 +14339,7 @@ unsigned int glsl_packAsImage4x4_comp_len = 3080; const unsigned char glsl_packAsImage4x4_TRANSPOSE_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x07, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x42, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x32, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, @@ -16714,101 +14351,74 @@ const unsigned char glsl_packAsImage4x4_TRANSPOSE_comp[] = { 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 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glsl_packAsImage4x4_TRANSPOSE_comp_len = 6008; +unsigned int glsl_packAsImage4x4_TRANSPOSE_comp_len = 3512; const unsigned char glsl_roipooling_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -18575,12 +16004,9 @@ const unsigned char glsl_resizeNearest_NEAREST_ROUND_comp[] = { 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xc2, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x03, 0x00, 0x09, 0x00, 0x00, 0x00, - 0x70, 0x6f, 0x73, 0x00, 0x05, 0x00, 0x08, 0x00, 0x0d, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, 0x0d, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, 0x44, 0x00, 0x00, 0x00, - 0x05, 0x00, 0x06, 0x00, 0x10, 0x00, 0x00, 0x00, 0x69, 0x6e, 0x70, 0x75, - 0x74, 0x49, 0x6d, 0x67, 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-unsigned int glsl_reduce_PROD_comp_len = 4168; +unsigned int glsl_reduce_PROD_comp_len = 2508; const unsigned char glsl_reduce_SUM_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xa3, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xb8, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -20653,55 +17191,26 @@ const unsigned char glsl_reduce_SUM_comp[] = { 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xc2, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, - 0x05, 0x00, 0x05, 0x00, 0x08, 0x00, 0x00, 0x00, 0x69, 0x6e, 0x69, 0x74, - 0x56, 0x61, 0x6c, 0x75, 0x65, 0x28, 0x00, 0x00, 0x05, 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0x0d, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x12, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x1e, 0x00, 0x04, 0x00, 0x13, 0x00, 0x00, 0x00, 0x12, 0x00, 0x00, 0x00, 0x12, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x14, 0x00, 0x00, 0x00, @@ -22970,23 +19183,19 @@ const unsigned char glsl_unPackImage4x4_TRANSPOSE_comp[] = { 0x02, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x14, 0x00, 0x02, 0x00, 0x34, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x38, 0x00, 0x00, 0x00, - 0x06, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, - 0x39, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x38, 0x00, 0x00, 0x00, - 0x16, 0x00, 0x03, 0x00, 0x4e, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, - 0x17, 0x00, 0x04, 0x00, 0x4f, 0x00, 0x00, 0x00, 0x4e, 0x00, 0x00, 0x00, - 0x04, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x50, 0x00, 0x00, 0x00, - 0x07, 0x00, 0x00, 0x00, 0x4f, 0x00, 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0x00, 0x3b, 0x00, 0x04, 0x00, @@ -22998,321 +19207,161 @@ const unsigned char glsl_unPackImage4x4_TRANSPOSE_comp[] = { 0x17, 0x00, 0x00, 0x00, 0x17, 0x00, 0x00, 0x00, 0x36, 0x00, 0x05, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x05, 0x00, 0x00, 0x00, - 0x3b, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, - 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x10, 0x00, 0x00, 0x00, - 0x11, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, - 0x10, 0x00, 0x00, 0x00, 0x1f, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, - 0x3b, 0x00, 0x04, 0x00, 0x10, 0x00, 0x00, 0x00, 0x25, 0x00, 0x00, 0x00, - 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x39, 0x00, 0x00, 0x00, - 0x3a, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, - 0x10, 0x00, 0x00, 0x00, 0x45, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, - 0x3b, 0x00, 0x04, 0x00, 0x50, 0x00, 0x00, 0x00, 0x51, 0x00, 0x00, 0x00, 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-unsigned int glsl_unPackImage4x4_TRANSPOSE_comp_len = 5224; +unsigned int glsl_unPackImage4x4_TRANSPOSE_comp_len = 3024; const unsigned char glsl_maxpool_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -24054,7 +20103,7 @@ unsigned int glsl_winogradTransformDest2_3_1_comp_len = 5772; const unsigned char glsl_winogradTransformDest2_3_1_RELU_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xbc, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x10, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -24065,10 +20114,7 @@ const unsigned char glsl_winogradTransformDest2_3_1_RELU_comp[] = { 0x08, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 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0x03, 0x00, 0x3b, 0x00, 0x00, 0x00, 0x36, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x3c, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x3c, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, @@ -24221,117 +20215,55 @@ const unsigned char glsl_winogradTransformDest2_3_1_RELU_comp[] = { 0x5a, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x16, 0x00, 0x03, 0x00, 0x70, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x71, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, - 0x20, 0x00, 0x04, 0x00, 0x72, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, - 0x71, 0x00, 0x00, 0x00, 0x19, 0x00, 0x09, 0x00, 0x74, 0x00, 0x00, 0x00, + 0x19, 0x00, 0x09, 0x00, 0x74, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x1b, 0x00, 0x03, 0x00, 0x75, 0x00, 0x00, 0x00, 0x74, 0x00, 0x00, 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0x00, 0x04, 0x00, 0x36, 0x00, 0x00, 0x00, + 0x40, 0x00, 0x00, 0x00, 0x3f, 0x00, 0x00, 0x00, 0x80, 0x00, 0x05, 0x00, + 0x36, 0x00, 0x00, 0x00, 0x41, 0x00, 0x00, 0x00, 0x3a, 0x00, 0x00, 0x00, + 0x40, 0x00, 0x00, 0x00, 0x51, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x43, 0x00, 0x00, 0x00, 0x35, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x14, 0x00, 0x00, 0x00, 0x45, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x44, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x46, 0x00, 0x00, 0x00, 0x45, 0x00, 0x00, 0x00, @@ -24339,565 +20271,337 @@ const unsigned char glsl_winogradTransformDest2_3_1_RELU_comp[] = { 0x43, 0x00, 0x00, 0x00, 0x46, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0x49, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x47, 0x00, 0x00, 0x00, 0x48, 0x00, 0x00, 0x00, 0x49, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x48, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, - 0x07, 0x00, 0x00, 0x00, 0x4b, 0x00, 0x00, 0x00, 0x33, 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0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x12, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -24908,10 +20612,7 @@ const unsigned char glsl_winogradTransformDest2_3_1_RELU6_comp[] = { 0x08, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xc2, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x06, 0x00, 0x0a, 0x00, 0x00, 0x00, - 0x43, 0x4c, 0x41, 0x4d, 0x50, 0x5f, 0x41, 0x44, 0x44, 0x28, 0x69, 0x31, - 0x3b, 0x00, 0x00, 0x00, 0x05, 0x00, 0x03, 0x00, 0x09, 0x00, 0x00, 0x00, - 0x78, 0x00, 0x00, 0x00, 0x05, 0x00, 0x05, 0x00, 0x0e, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x05, 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glsl_winogradTransformDest2_3_1_RELU6_comp_len = 5988; const unsigned char glsl_winogradTransformSource2_3_1_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -28053,7 +23412,7 @@ unsigned int glsl_imageTonc4hw4_comp_len = 2220; const unsigned char glsl_binary_blit_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xa2, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x16, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -28064,61 +23423,24 @@ const unsigned char glsl_binary_blit_comp[] = { 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 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0x00, 0x06, 0x00, 0x92, 0x00, 0x00, 0x00, 0xa2, 0x00, 0x00, 0x00, + 0x8b, 0x00, 0x00, 0x00, 0x71, 0x00, 0x00, 0x00, 0xef, 0x00, 0x00, 0x00, + 0x3e, 0x00, 0x03, 0x00, 0xa2, 0x00, 0x00, 0x00, 0xa1, 0x00, 0x00, 0x00, + 0xf9, 0x00, 0x02, 0x00, 0x50, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x50, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_binary_blit_ADD_comp_len = 4292; +unsigned int glsl_binary_blit_ADD_comp_len = 2808; const unsigned char glsl_binary_blit_SUB_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xa5, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xf6, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -28783,44 +23812,19 @@ const unsigned char glsl_binary_blit_SUB_comp[] = { 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0c, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6d, 0x70, 0x75, 0x74, 0x65, 0x56, - 0x65, 0x63, 0x34, 0x64, 0x6f, 0x74, 0x28, 0x76, 0x69, 0x34, 0x3b, 0x76, - 0x69, 0x34, 0x3b, 0x00, 0x05, 0x00, 0x03, 0x00, 0x0a, 0x00, 0x00, 0x00, - 0x61, 0x00, 0x00, 0x00, 0x05, 0x00, 0x03, 0x00, 0x0b, 0x00, 0x00, 0x00, - 0x62, 0x00, 0x00, 0x00, 0x05, 0x00, 0x06, 0x00, 0x14, 0x00, 0x00, 0x00, - 0x62, 0x69, 0x6e, 0x61, 0x72, 0x79, 0x28, 0x76, 0x66, 0x34, 0x3b, 0x76, - 0x66, 0x34, 0x3b, 0x00, 0x05, 0x00, 0x03, 0x00, 0x12, 0x00, 0x00, 0x00, - 0x78, 0x30, 0x00, 0x00, 0x05, 0x00, 0x03, 0x00, 0x13, 0x00, 0x00, 0x00, - 0x78, 0x31, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x35, 0x00, 0x00, 0x00, - 0x76, 0x61, 0x6c, 0x75, 0x65, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, - 0x3e, 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0x00, 0x03, 0x00, 0xa2, 0x00, 0x00, 0x00, 0xa1, 0x00, 0x00, 0x00, + 0xf9, 0x00, 0x02, 0x00, 0x50, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x50, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_binary_blit_SUB_comp_len = 4292; +unsigned int glsl_binary_blit_SUB_comp_len = 2808; const unsigned char glsl_binary_blit_MUL_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xa5, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xf6, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -29145,44 +24050,19 @@ const unsigned char glsl_binary_blit_MUL_comp[] = { 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 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0x00, 0x02, 0x00, 0x50, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x50, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_binary_blit_MUL_comp_len = 4292; +unsigned int glsl_binary_blit_MUL_comp_len = 2808; const unsigned char glsl_binary_blit_DIV_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xa5, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xf6, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -29507,44 +24288,19 @@ const unsigned char glsl_binary_blit_DIV_comp[] = { 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 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0x00, 0x00, 0x00, 0x00, @@ -29559,306 +24315,207 @@ const unsigned char glsl_binary_blit_DIV_comp[] = { 0x65, 0x72, 0x30, 0x00, 0x06, 0x00, 0x05, 0x00, 0x97, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x64, 0x61, 0x74, 0x61, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x99, 0x00, 0x00, 0x00, 0x75, 0x49, 0x6e, 0x70, - 0x75, 0x74, 0x31, 0x00, 0x05, 0x00, 0x04, 0x00, 0x9e, 0x00, 0x00, 0x00, - 0x70, 0x61, 0x72, 0x61, 0x6d, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, - 0x9f, 0x00, 0x00, 0x00, 0x70, 0x61, 0x72, 0x61, 0x6d, 0x00, 0x00, 0x00, - 0x47, 0x00, 0x04, 0x00, 0x41, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x00, 0x00, - 0x1c, 0x00, 0x00, 0x00, 0x48, 0x00, 0x05, 0x00, 0x46, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x23, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x48, 0x00, 0x05, 0x00, 0x46, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x23, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x48, 0x00, 0x05, 0x00, - 0x46, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x23, 0x00, 0x00, 0x00, - 0x20, 0x00, 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-unsigned int glsl_binary_blit_DIV_comp_len = 4292; +unsigned int glsl_binary_blit_DIV_comp_len = 2808; const unsigned char glsl_binary_blit_POW_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xa5, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xf6, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -29869,44 +24526,19 @@ const unsigned char glsl_binary_blit_POW_comp[] = { 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0c, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6d, 0x70, 0x75, 0x74, 0x65, 0x56, - 0x65, 0x63, 0x34, 0x64, 0x6f, 0x74, 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= 4300; +unsigned int glsl_binary_blit_POW_comp_len = 2816; const unsigned char glsl_binary_blit_VMAX_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xa5, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xf6, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -30232,44 +24765,19 @@ const unsigned char glsl_binary_blit_VMAX_comp[] = { 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0c, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6d, 0x70, 0x75, 0x74, 0x65, 0x56, - 0x65, 0x63, 0x34, 0x64, 0x6f, 0x74, 0x28, 0x76, 0x69, 0x34, 0x3b, 0x76, - 0x69, 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glsl_binary_blit_VMAX_comp_len = 2816; const unsigned char glsl_binary_blit_VMIN_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xa5, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xf6, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -30595,44 +25004,19 @@ const unsigned char glsl_binary_blit_VMIN_comp[] = { 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0c, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6d, 0x70, 0x75, 0x74, 0x65, 0x56, - 0x65, 0x63, 0x34, 0x64, 0x6f, 0x74, 0x28, 0x76, 0x69, 0x34, 0x3b, 0x76, - 0x69, 0x34, 0x3b, 0x00, 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unsigned char glsl_binary_blit_SQUDIFF_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xa9, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0xfe, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -30958,44 +25243,19 @@ const unsigned char glsl_binary_blit_SQUDIFF_comp[] = { 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0c, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6d, 0x70, 0x75, 0x74, 0x65, 0x56, - 0x65, 0x63, 0x34, 0x64, 0x6f, 0x74, 0x28, 0x76, 0x69, 0x34, 0x3b, 0x76, - 0x69, 0x34, 0x3b, 0x00, 0x05, 0x00, 0x03, 0x00, 0x0a, 0x00, 0x00, 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0x00, 0x01, 0x00 +}; +unsigned int glsl_convolutionDepthwise_s1d1_w2_RELU_comp_len = 6932; + +const unsigned char glsl_convolutionDepthwise_s1d1_w2_RELU6_comp[] = { + 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, + 0x1d, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, + 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, + 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, + 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x0f, 0x00, 0x06, 0x00, 0x05, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, + 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00, + 0x10, 0x00, 0x06, 0x00, 0x04, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00, + 0x08, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, + 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, + 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x06, 0x00, 0x08, 0x00, 0x00, 0x00, + 0x6f, 0x75, 0x74, 0x70, 0x75, 0x74, 0x49, 0x6e, 0x64, 0x65, 0x78, 0x57, + 0x32, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x00, 0x00, + 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, 0x6c, 0x49, 0x6e, 0x76, + 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, 0x44, 0x00, 0x00, 0x00, + 0x05, 0x00, 0x06, 0x00, 0x12, 0x00, 0x00, 0x00, 0x6f, 0x75, 0x74, 0x70, + 0x75, 0x74, 0x49, 0x6e, 0x64, 0x65, 0x78, 0x48, 0x00, 0x00, 0x00, 0x00, + 0x05, 0x00, 0x05, 0x00, 0x17, 0x00, 0x00, 0x00, 0x6f, 0x75, 0x74, 0x70, + 0x75, 0x74, 0x57, 0x32, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x05, 0x00, 0x1a, 0x00, 0x00, 0x00, 0x63, 0x6f, 0x6e, 0x73, 0x74, 0x42, 0x75, 0x66, 0x66, 0x65, 0x72, 0x00, 0x06, 0x00, 0x04, 0x00, 0x1a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x70, 0x61, 0x64, 0x00, 0x06, 0x00, 0x06, 0x00, @@ -31740,781 +26662,554 @@ const unsigned char 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= 4820; +unsigned int glsl_convolutionDepthwise_s1d1_w2_RELU6_comp_len = 6984; const unsigned char glsl_matmul_output_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -32747,39 +27442,20 @@ const unsigned char glsl_matmul_output_BIAS_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, - 0x70, 0x6f, 0x73, 0x58, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0c, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, - 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, - 0x44, 0x00, 0x00, 0x00, 0x05, 0x00, 0x06, 0x00, 0x17, 0x00, 0x00, 0x00, - 0x6f, 0x66, 0x66, 0x73, 0x65, 0x74, 0x42, 0x75, 0x66, 0x66, 0x65, 0x72, - 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x05, 0x00, 0x17, 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0x00, 0x00, 0x00, 0x47, 0x00, 0x03, 0x00, 0xa3, 0x00, 0x00, 0x00, + 0x19, 0x00, 0x00, 0x00, 0x47, 0x00, 0x04, 0x00, 0xd1, 0x00, 0x00, 0x00, + 0x0b, 0x00, 0x00, 0x00, 0x19, 0x00, 0x00, 0x00, 0x13, 0x00, 0x02, 0x00, + 0x02, 0x00, 0x00, 0x00, 0x21, 0x00, 0x03, 0x00, 0x03, 0x00, 0x00, 0x00, + 0x02, 0x00, 0x00, 0x00, 0x15, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x20, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x15, 0x00, 0x04, 0x00, 0x09, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x0b, 0x00, 0x00, 0x00, @@ -33220,24 +27735,20 @@ const unsigned char glsl_matmul_output_TRANSPOSE_comp[] = { 0x03, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x02, 0x00, 0x1f, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x23, 0x00, 0x00, 0x00, - 0x06, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 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0x00, 0x04, 0x00, 0x00, 0x00, + 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x47, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x53, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, + 0x06, 0x00, 0x00, 0x00, 0x5f, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x09, 0x00, 0x00, 0x00, 0x7c, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x14, 0x00, 0x00, 0x00, 0x97, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, @@ -33251,203 +27762,103 @@ const unsigned char glsl_matmul_output_TRANSPOSE_comp[] = { 0xa2, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xa1, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0xa2, 0x00, 0x00, 0x00, 0xa3, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x2c, 0x00, 0x05, 0x00, 0x23, 0x00, 0x00, 0x00, - 0xa6, 0x00, 0x00, 0x00, 0x1a, 0x00, 0x00, 0x00, 0x1a, 0x00, 0x00, 0x00, - 0x2c, 0x00, 0x05, 0x00, 0x23, 0x00, 0x00, 0x00, 0xb3, 0x00, 0x00, 0x00, - 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0x02, 0x00, 0x22, 0x00, 0x00, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x22, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, + 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_matmul_output_TRANSPOSE_comp_len = 4724; +unsigned int glsl_matmul_output_TRANSPOSE_comp_len = 2992; const unsigned char glsl_matmul_output_TRANSPOSE_BIAS_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -33548,39 +27932,20 @@ const unsigned char glsl_matmul_output_TRANSPOSE_BIAS_comp[] = { 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, - 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, - 0x70, 0x6f, 0x73, 0x58, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x08, 0x00, - 0x0c, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, - 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, - 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0x2b, 0x00, 0x04, 0x00, 0x29, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x2c, 0x00, 0x07, 0x00, 0x2a, 0x00, 0x00, 0x00, - 0x2e, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, - 0x2d, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, - 0x0a, 0x00, 0x00, 0x00, 0x33, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, - 0x19, 0x00, 0x09, 0x00, 0x53, 0x00, 0x00, 0x00, 0x29, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x1b, 0x00, 0x03, 0x00, 0x54, 0x00, 0x00, 0x00, 0x53, 0x00, 0x00, 0x00, - 0x20, 0x00, 0x04, 0x00, 0x55, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x54, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x55, 0x00, 0x00, 0x00, - 0x56, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, - 0x06, 0x00, 0x00, 0x00, 0x58, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, - 0x17, 0x00, 0x04, 0x00, 0x5d, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, - 0x02, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, - 0x6a, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, - 0x06, 0x00, 0x00, 0x00, 0x79, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, - 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, - 0x03, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x55, 0x00, 0x00, 0x00, - 0x94, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x19, 0x00, 0x09, 0x00, + 0x20, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x2a, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x29, 0x00, 0x00, 0x00, + 0x2d, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x2c, 0x00, 0x07, 0x00, + 0x2a, 0x00, 0x00, 0x00, 0x2e, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, + 0x2d, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, + 0x2b, 0x00, 0x04, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x33, 0x00, 0x00, 0x00, + 0x03, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x0a, 0x00, 0x00, 0x00, + 0x39, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x19, 0x00, 0x09, 0x00, + 0x53, 0x00, 0x00, 0x00, 0x29, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x03, 0x00, + 0x54, 0x00, 0x00, 0x00, 0x53, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, + 0x55, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x54, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x55, 0x00, 0x00, 0x00, 0x56, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x58, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, + 0x5d, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, + 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x6a, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x79, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, + 0x06, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x55, 0x00, 0x00, 0x00, 0x94, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0xce, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x29, 0x00, 0x00, 0x00, 0x19, 0x00, 0x09, 0x00, 0x2f, 0x01, 0x00, 0x00, 0x29, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, @@ -34087,11 +28312,36 @@ const unsigned char glsl_gemm16x16_comp[] = { 0x52, 0x01, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x36, 0x00, 0x05, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x05, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x00, 0x00, - 0x0d, 0x00, 0x00, 0x00, 0x7c, 0x00, 0x04, 0x00, 0x07, 0x00, 0x00, 0x00, - 0x0f, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x51, 0x00, 0x05, 0x00, - 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, 0x1a, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0x2c, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x2b, 0x00, 0x00, 0x00, 0x2f, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x30, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0x31, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x12, 0x00, 0x00, 0x00, 0x32, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x12, 0x00, 0x00, 0x00, 0x36, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x12, 0x00, 0x00, 0x00, + 0x40, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x12, 0x00, 0x00, 0x00, 0x49, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x52, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0x66, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x2b, 0x00, 0x00, 0x00, 0x75, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0x93, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x2b, 0x00, 0x00, 0x00, 0xa2, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, 0xb0, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0xbe, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, + 0x0b, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x0d, 0x00, 0x00, 0x00, + 0x7c, 0x00, 0x04, 0x00, 0x07, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x00, 0x00, + 0x0e, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x09, 0x00, 0x00, 0x00, + 0x0f, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x12, 0x00, 0x00, 0x00, + 0x13, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00, + 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, + 0x13, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, 0x1a, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x19, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x00, 0x00, 0xb1, 0x00, 0x05, 0x00, @@ -34099,222 +28349,478 @@ const unsigned char glsl_gemm16x16_comp[] = { 0x1c, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0x1f, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x1d, 0x00, 0x00, 0x00, 0x1e, 0x00, 0x00, 0x00, 0x1f, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x1e, 0x00, 0x00, 0x00, 0x51, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, - 0x22, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x41, 0x00, 0x06, 0x00, 0x1a, 0x00, 0x00, 0x00, 0x23, 0x00, 0x00, 0x00, - 0x18, 0x00, 0x00, 0x00, 0x19, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, - 0x23, 0x00, 0x00, 0x00, 0xb1, 0x00, 0x05, 0x00, 0x10, 0x00, 0x00, 0x00, - 0x25, 0x00, 0x00, 0x00, 0x22, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, - 0xf9, 0x00, 0x02, 0x00, 0x1f, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x1f, 0x00, 0x00, 0x00, 0xf5, 0x00, 0x07, 0x00, 0x10, 0x00, 0x00, 0x00, - 0x26, 0x00, 0x00, 0x00, 0x1d, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, - 0x25, 0x00, 0x00, 0x00, 0x1e, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, - 0x28, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, - 0x26, 0x00, 0x00, 0x00, 0x27, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x27, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, - 0x1a, 0x00, 0x00, 0x00, 0x34, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, - 0x19, 0x00, 0x00, 0x00, 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0x0b, 0x00, 0x08, 0x00, - 0x59, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x3a, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x09, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, @@ -34329,6 +28835,7 @@ const unsigned char glsl_gemm16x16_FP16_comp[] = { 0x68, 0x61, 0x64, 0x65, 0x72, 0x5f, 0x68, 0x61, 0x6c, 0x66, 0x5f, 0x66, 0x6c, 0x6f, 0x61, 0x74, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, + 0x05, 0x00, 0x03, 0x00, 0x09, 0x00, 0x00, 0x00, 0x70, 0x6f, 0x73, 0x00, 0x05, 0x00, 0x08, 0x00, 0x0d, 0x00, 0x00, 0x00, 0x67, 0x6c, 0x5f, 0x47, 0x6c, 0x6f, 0x62, 0x61, 0x6c, 0x49, 0x6e, 0x76, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x49, 0x44, 0x00, 0x00, 0x00, 0x05, 0x00, 0x05, 0x00, @@ -34336,40 +28843,60 @@ const 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0x00, 0x00, 0x15, 0x00, 0x04, 0x00, + 0x0a, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x17, 0x00, 0x04, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, + 0x03, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x0c, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x0c, 0x00, 0x00, 0x00, 0x0d, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x14, 0x00, 0x02, 0x00, 0x10, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, + 0x0a, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x20, 0x00, 0x04, 0x00, 0x12, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x06, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x15, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x1e, 0x00, 0x03, 0x00, 0x16, 0x00, 0x00, 0x00, 0x15, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x17, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x16, 0x00, 0x00, 0x00, @@ -34380,29 +28907,33 @@ const unsigned char glsl_gemm16x16_FP16_comp[] = { 0x2b, 0x00, 0x04, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x16, 0x00, 0x03, 0x00, 0x29, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x2a, 0x00, 0x00, 0x00, - 0x29, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, - 0x29, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x2c, 0x00, 0x07, 0x00, 0x2a, 0x00, 0x00, 0x00, 0x2e, 0x00, 0x00, 0x00, - 0x2d, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, - 0x2d, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x0a, 0x00, 0x00, 0x00, - 0x33, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x16, 0x00, 0x03, 0x00, - 0x53, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x19, 0x00, 0x09, 0x00, - 0x54, 0x00, 0x00, 0x00, 0x53, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x03, 0x00, - 0x55, 0x00, 0x00, 0x00, 0x54, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, - 0x56, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x55, 0x00, 0x00, 0x00, - 0x3b, 0x00, 0x04, 0x00, 0x56, 0x00, 0x00, 0x00, 0x57, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, - 0x59, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, - 0x5e, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, - 0x17, 0x00, 0x04, 0x00, 0x61, 0x00, 0x00, 0x00, 0x53, 0x00, 0x00, 0x00, - 0x04, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, - 0x68, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, - 0x06, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, - 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x7e, 0x00, 0x00, 0x00, - 0x03, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x56, 0x00, 0x00, 0x00, - 0x86, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x19, 0x00, 0x09, 0x00, + 0x29, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, + 0x2b, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x2a, 0x00, 0x00, 0x00, + 0x2b, 0x00, 0x04, 0x00, 0x29, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x2c, 0x00, 0x07, 0x00, 0x2a, 0x00, 0x00, 0x00, + 0x2e, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, + 0x2d, 0x00, 0x00, 0x00, 0x2d, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, + 0x0a, 0x00, 0x00, 0x00, 0x33, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, + 0x2b, 0x00, 0x04, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x39, 0x00, 0x00, 0x00, + 0x02, 0x00, 0x00, 0x00, 0x16, 0x00, 0x03, 0x00, 0x53, 0x00, 0x00, 0x00, + 0x20, 0x00, 0x00, 0x00, 0x19, 0x00, 0x09, 0x00, 0x54, 0x00, 0x00, 0x00, + 0x53, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x03, 0x00, 0x55, 0x00, 0x00, 0x00, + 0x54, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x56, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x55, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x56, 0x00, 0x00, 0x00, 0x57, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x59, 0x00, 0x00, 0x00, + 0x04, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, 0x5e, 0x00, 0x00, 0x00, + 0x06, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, + 0x61, 0x00, 0x00, 0x00, 0x53, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, + 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x73, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, + 0x06, 0x00, 0x00, 0x00, 0x7e, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x56, 0x00, 0x00, 0x00, 0x86, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0xb0, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x29, 0x00, 0x00, 0x00, 0x19, 0x00, 0x09, 0x00, 0x11, 0x01, 0x00, 0x00, 0x53, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, @@ -34414,11 +28945,36 @@ const unsigned char glsl_gemm16x16_FP16_comp[] = { 0x38, 0x01, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x36, 0x00, 0x05, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x05, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x00, 0x00, - 0x0d, 0x00, 0x00, 0x00, 0x7c, 0x00, 0x04, 0x00, 0x07, 0x00, 0x00, 0x00, - 0x0f, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x51, 0x00, 0x05, 0x00, - 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, 0x1a, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0x2c, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x2b, 0x00, 0x00, 0x00, 0x2f, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x30, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0x31, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x12, 0x00, 0x00, 0x00, 0x32, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x12, 0x00, 0x00, 0x00, 0x36, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x12, 0x00, 0x00, 0x00, + 0x40, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x12, 0x00, 0x00, 0x00, 0x49, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x52, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0x64, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x2b, 0x00, 0x00, 0x00, 0x6f, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x7a, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0x85, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x2b, 0x00, 0x00, 0x00, 0x90, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, + 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x9a, 0x00, 0x00, 0x00, + 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x2b, 0x00, 0x00, 0x00, + 0xa4, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, + 0x0b, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x0d, 0x00, 0x00, 0x00, + 0x7c, 0x00, 0x04, 0x00, 0x07, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x00, 0x00, + 0x0e, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x09, 0x00, 0x00, 0x00, + 0x0f, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x12, 0x00, 0x00, 0x00, + 0x13, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00, + 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, + 0x13, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, 0x1a, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x19, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x00, 0x00, 0xb1, 0x00, 0x05, 0x00, @@ -34426,234 +28982,418 @@ const unsigned char glsl_gemm16x16_FP16_comp[] = { 0x1c, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, 0x1f, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, 0x1d, 0x00, 0x00, 0x00, 0x1e, 0x00, 0x00, 0x00, 0x1f, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x1e, 0x00, 0x00, 0x00, 0x51, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, - 0x22, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x41, 0x00, 0x06, 0x00, 0x1a, 0x00, 0x00, 0x00, 0x23, 0x00, 0x00, 0x00, - 0x18, 0x00, 0x00, 0x00, 0x19, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, - 0x23, 0x00, 0x00, 0x00, 0xb1, 0x00, 0x05, 0x00, 0x10, 0x00, 0x00, 0x00, - 0x25, 0x00, 0x00, 0x00, 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glsl_gemm16x16_FP16_comp_len = 6868; const unsigned char glsl_deconvolutionDepthwise_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -35002,7 +29742,7 @@ unsigned int glsl_deconvolutionDepthwise_comp_len = 4084; const unsigned char glsl_deconvolutionDepthwise_RELU_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0xee, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x09, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ -35013,47 +29753,28 @@ const unsigned char glsl_deconvolutionDepthwise_RELU_comp[] = { 0x08, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xc2, 0x01, 0x00, 0x00, 0x05, 0x00, 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0xd9, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x32, 0x00, 0x00, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x32, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, + 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_deconvolutionDepthwise_RELU6_comp_len = 5816; +unsigned int glsl_deconvolutionDepthwise_RELU6_comp_len = 4204; const unsigned char glsl_preluWithChannel_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -36497,7 +30969,7 @@ unsigned int glsl_deconvIm2Col_comp_len = 4172; const unsigned char glsl_deconvIm2Col_RELU_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x18, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x3d, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, @@ 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0x00, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x65, 0x00, 0x00, 0x00, + 0x02, 0x00, 0x00, 0x00, 0x15, 0x00, 0x00, 0x00, 0x16, 0x00, 0x03, 0x00, + 0x69, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x17, 0x00, 0x04, 0x00, + 0x6a, 0x00, 0x00, 0x00, 0x69, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x19, 0x00, 0x09, 0x00, 0x6d, 0x00, 0x00, 0x00, 0x69, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -37210,412 +31452,240 @@ const unsigned char glsl_deconvIm2Col_RELU6_comp[] = { 0x19, 0x01, 0x00, 0x00, 0x18, 0x01, 0x00, 0x00, 0x27, 0x00, 0x00, 0x00, 0x27, 0x00, 0x00, 0x00, 0x36, 0x00, 0x05, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x05, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, - 0x08, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, - 0x3b, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 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glsl_deconvIm2Col_RELU6_comp_len = 6704; +unsigned int glsl_deconvIm2Col_RELU6_comp_len = 4292; const unsigned char glsl_buffer2Image1D_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, @@ -38092,7 +32162,7 @@ unsigned int glsl_argmax_comp_len = 2096; const unsigned char glsl_argmax_ARGMIN_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, - 0x77, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x8b, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, @@ -38102,82 +32172,66 @@ const unsigned char glsl_argmax_ARGMIN_comp[] = { 0x11, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 0xb8, 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0x00, 0x00, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, + 0x0c, 0x00, 0x00, 0x00, 0x0d, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x16, 0x00, 0x03, 0x00, 0x17, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x1e, 0x00, 0x06, 0x00, 0x18, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x17, 0x00, 0x00, 0x00, @@ -38191,165 +32245,99 @@ const unsigned char glsl_argmax_ARGMIN_comp[] = { 0x28, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x32, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x3f, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x20, 0x00, 0x04, 0x00, 0x46, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, - 0x17, 0x00, 0x00, 0x00, 0x1d, 0x00, 0x03, 0x00, 0x48, 0x00, 0x00, 0x00, - 0x17, 0x00, 0x00, 0x00, 0x1e, 0x00, 0x03, 0x00, 0x49, 0x00, 0x00, 0x00, - 0x48, 0x00, 0x00, 0x00, 0x20, 0x00, 0x04, 0x00, 0x4a, 0x00, 0x00, 0x00, - 0x02, 0x00, 0x00, 0x00, 0x49, 0x00, 0x00, 0x00, 0x3b, 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0x05, 0x00, + 0x06, 0x00, 0x00, 0x00, 0x42, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x00, 0x00, + 0x41, 0x00, 0x00, 0x00, 0x80, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x45, 0x00, 0x00, 0x00, 0x42, 0x00, 0x00, 0x00, 0x25, 0x00, 0x00, 0x00, + 0x41, 0x00, 0x06, 0x00, 0x4d, 0x00, 0x00, 0x00, 0x4e, 0x00, 0x00, 0x00, + 0x4b, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x00, 0x00, 0x45, 0x00, 0x00, 0x00, + 0x3d, 0x00, 0x04, 0x00, 0x17, 0x00, 0x00, 0x00, 0x4f, 0x00, 0x00, 0x00, + 0x4e, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x52, 0x00, 0x00, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x52, 0x00, 0x00, 0x00, 0xf5, 0x00, 0x07, 0x00, + 0x17, 0x00, 0x00, 0x00, 0x85, 0x00, 0x00, 0x00, 0x4f, 0x00, 0x00, 0x00, + 0x37, 0x00, 0x00, 0x00, 0x89, 0x00, 0x00, 0x00, 0x55, 0x00, 0x00, 0x00, + 0xf5, 0x00, 0x07, 0x00, 0x06, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, + 0x1b, 0x00, 0x00, 0x00, 0x37, 0x00, 0x00, 0x00, 0x8a, 0x00, 0x00, 0x00, + 0x55, 0x00, 0x00, 0x00, 0xf5, 0x00, 0x07, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x83, 0x00, 0x00, 0x00, 0x3f, 0x00, 0x00, 0x00, 0x37, 0x00, 0x00, 0x00, + 0x6c, 0x00, 0x00, 0x00, 0x55, 0x00, 0x00, 0x00, 0xb1, 0x00, 0x05, 0x00, + 0x28, 0x00, 0x00, 0x00, 0x5a, 0x00, 0x00, 0x00, 0x83, 0x00, 0x00, 0x00, + 0x41, 0x00, 0x00, 0x00, 0xf6, 0x00, 0x04, 0x00, 0x54, 0x00, 0x00, 0x00, + 0x55, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, + 0x5a, 0x00, 0x00, 0x00, 0x53, 0x00, 0x00, 0x00, 0x54, 0x00, 0x00, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x53, 0x00, 0x00, 0x00, 0x84, 0x00, 0x05, 0x00, + 0x06, 0x00, 0x00, 0x00, 0x60, 0x00, 0x00, 0x00, 0x83, 0x00, 0x00, 0x00, + 0x1e, 0x00, 0x00, 0x00, 0x80, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x61, 0x00, 0x00, 0x00, 0x45, 0x00, 0x00, 0x00, 0x60, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, 0x4d, 0x00, 0x00, 0x00, 0x62, 0x00, 0x00, 0x00, 0x4b, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x00, 0x00, 0x61, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x17, 0x00, 0x00, 0x00, 0x63, 0x00, 0x00, 0x00, - 0x62, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x5b, 0x00, 0x00, 0x00, - 0x63, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x17, 0x00, 0x00, 0x00, - 0x64, 0x00, 0x00, 0x00, 0x5b, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, - 0x17, 0x00, 0x00, 0x00, 0x65, 0x00, 0x00, 0x00, 0x47, 0x00, 0x00, 0x00, - 0xb8, 0x00, 0x05, 0x00, 0x28, 0x00, 0x00, 0x00, 0x66, 0x00, 0x00, 0x00, - 0x64, 0x00, 0x00, 0x00, 0x65, 0x00, 0x00, 0x00, 0xf7, 0x00, 0x03, 0x00, - 0x68, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xfa, 0x00, 0x04, 0x00, - 0x66, 0x00, 0x00, 0x00, 0x67, 0x00, 0x00, 0x00, 0x68, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x67, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, - 0x17, 0x00, 0x00, 0x00, 0x69, 0x00, 0x00, 0x00, 0x5b, 0x00, 0x00, 0x00, - 0x3e, 0x00, 0x03, 0x00, 0x47, 0x00, 0x00, 0x00, 0x69, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x6a, 0x00, 0x00, 0x00, - 0x51, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x50, 0x00, 0x00, 0x00, - 0x6a, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x68, 0x00, 0x00, 0x00, - 0xf8, 0x00, 0x02, 0x00, 0x68, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, - 0x55, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x55, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, - 0x51, 0x00, 0x00, 0x00, 0x80, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, - 0x6c, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00, 0x3f, 0x00, 0x00, 0x00, - 0x3e, 0x00, 0x03, 0x00, 0x51, 0x00, 0x00, 0x00, 0x6c, 0x00, 0x00, 0x00, - 0xf9, 0x00, 0x02, 0x00, 0x52, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, - 0x54, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x14, 0x00, 0x00, 0x00, - 0x71, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x13, 0x00, 0x00, 0x00, - 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x72, 0x00, 0x00, 0x00, - 0x71, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, - 0x73, 0x00, 0x00, 0x00, 0x50, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, + 0x62, 0x00, 0x00, 0x00, 0xb8, 0x00, 0x05, 0x00, 0x28, 0x00, 0x00, 0x00, + 0x66, 0x00, 0x00, 0x00, 0x63, 0x00, 0x00, 0x00, 0x85, 0x00, 0x00, 0x00, + 0xf9, 0x00, 0x02, 0x00, 0x68, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, + 0x68, 0x00, 0x00, 0x00, 0xa9, 0x00, 0x06, 0x00, 0x17, 0x00, 0x00, 0x00, + 0x89, 0x00, 0x00, 0x00, 0x66, 0x00, 0x00, 0x00, 0x63, 0x00, 0x00, 0x00, + 0x85, 0x00, 0x00, 0x00, 0xa9, 0x00, 0x06, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x8a, 0x00, 0x00, 0x00, 0x66, 0x00, 0x00, 0x00, 0x83, 0x00, 0x00, 0x00, + 0x84, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x55, 0x00, 0x00, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x55, 0x00, 0x00, 0x00, 0x80, 0x00, 0x05, 0x00, + 0x06, 0x00, 0x00, 0x00, 0x6c, 0x00, 0x00, 0x00, 0x83, 0x00, 0x00, 0x00, + 0x3f, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x52, 0x00, 0x00, 0x00, + 0xf8, 0x00, 0x02, 0x00, 0x54, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x74, 0x00, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, - 0x1b, 0x00, 0x00, 0x00, 0x72, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, - 0x74, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, + 0x1b, 0x00, 0x00, 0x00, 0x16, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, + 0x74, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, 0xf9, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x38, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 }; -unsigned int glsl_argmax_ARGMIN_comp_len = 3080; +unsigned int glsl_argmax_ARGMIN_comp_len = 2096; const unsigned char glsl_buffer2Image3D_comp[] = { 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0b, 0x00, 0x08, 0x00, diff --git a/source/backend/vulkan/image/execution/VulkanConvolution.cpp b/source/backend/vulkan/image/execution/VulkanConvolution.cpp index bc2780545..ca43921b1 100644 --- a/source/backend/vulkan/image/execution/VulkanConvolution.cpp +++ b/source/backend/vulkan/image/execution/VulkanConvolution.cpp @@ -121,11 +121,11 @@ bool VulkanConvolutionDepthwise::_init(const float* weightData, size_t weightSiz auto macro = getPostTreatMacro(common); if (common->strideX() == 1 && common->strideY() == 1 && common->dilateX() == 1 && common->dilateY() == 1 ) { mConvPipeline = extra->getPipeline("glsl_convolutionDepthwise_s1d1_w2_" + macro + "comp", convTypes); + mUseS1D1W2 = true; mLocalX = 8; mLocalY = 8; } else { if (extra->gpuType() == VulkanRuntime::ADRENO) { - MNN_PRINT("S1D1 depthwise conv!\n"); mConvPipeline = extra->getPipeline("glsl_convolutionDepthwise_" + macro + "comp", convTypes); mLocalX = 16; mLocalY = 16; @@ -236,7 +236,11 @@ ErrorCode VulkanConvolutionDepthwise::onEncodeConvolution(const Convolution2DCom mBias->barrierRead(cmdBuffer->get()); ((VulkanTensor*)input->deviceId())->image()->barrierRead(cmdBuffer->get()); ((VulkanTensor*)output->deviceId())->image()->barrierWrite(cmdBuffer->get()); - vkCmdDispatch(cmdBuffer->get(), UP_DIV(ow, mLocalX), UP_DIV(oh, mLocalY), ocDiv4 * input->batch()); + if (mUseS1D1W2) { + vkCmdDispatch(cmdBuffer->get(), UP_DIV(UP_DIV(ow, 2), mLocalX), UP_DIV(oh, mLocalY), ocDiv4 * input->batch()); + } else { + vkCmdDispatch(cmdBuffer->get(), UP_DIV(ow, mLocalX), UP_DIV(oh, mLocalY), ocDiv4 * input->batch()); + } return NO_ERROR; } diff --git a/source/backend/vulkan/image/execution/VulkanConvolution.hpp b/source/backend/vulkan/image/execution/VulkanConvolution.hpp index 162d94918..9f49fc2b8 100644 --- a/source/backend/vulkan/image/execution/VulkanConvolution.hpp +++ b/source/backend/vulkan/image/execution/VulkanConvolution.hpp @@ -102,6 +102,7 @@ class VulkanConvolutionDepthwise : public VulkanConvolutionCommon { int mLocalX = 0; int mLocalY = 0; + bool mUseS1D1W2 = false; }; } // namespace MNN diff --git a/source/backend/vulkan/image/execution/glsl/convolutionDepthwise_s1d1_w2.comp b/source/backend/vulkan/image/execution/glsl/convolutionDepthwise_s1d1_w2.comp index 208eccea3..4bc4b0e66 100644 --- a/source/backend/vulkan/image/execution/glsl/convolutionDepthwise_s1d1_w2.comp +++ b/source/backend/vulkan/image/execution/glsl/convolutionDepthwise_s1d1_w2.comp @@ -19,7 +19,7 @@ layout(set=0, binding=4) readonly uniform constBuffer { #define UP_DIV(x, y) (((x)+(y)-1)/(y)) -layout (local_size_x = 8, local_size_y = 8, local_size_z_id = 2) in; +layout (local_size_x = 8, local_size_y = 8, local_size_z = 1) in; void main() { @@ -29,21 +29,22 @@ void main() int outputW2 = UP_DIV(uConstant.outputSize.x, 2); - if (outputIndexW2 < outputW2 && outputIndexH < uConstant.outputSize.y) { + if (outputIndexW2 >= outputW2 || outputIndexH >= uConstant.outputSize.y) { + return; + } int outputIndexNC4 = int(gl_GlobalInvocationID.z); int outputIndexC4 = outputIndexNC4 % uConstant.outputSize.z; int outputIndexN = outputIndexNC4 / uConstant.outputSize.z; - ivec2 inputIndexOffset = ivec2(outputIndexW2 * 2, outputIndexH) - uConstant.pad; - int inputIndexStartH = max(0, -inputIndexOffset.y); - int inputIndexEndH = min(uConstant.kernelSize.y, uConstant.inputSize.y - inputIndexOffset.y); - vec4 result0 = texelFetch(uBias, ivec2(outputIndexC4, 0), 0); vec4 result1 = result0; + ivec2 inputIndexOffset = ivec2(outputIndexW2 * 2 - uConstant.pad.x, outputIndexH - uConstant.pad.y); + int inputIndexStartH = max(0, -inputIndexOffset.y); + int inputIndexEndH = min(uConstant.kernelSize.y, uConstant.inputSize.y - inputIndexOffset.y); + // accumulate result - vec2 inputImageSize = textureSize(uInput, 0); for (int kernelIndexH = inputIndexStartH; kernelIndexH < inputIndexEndH; kernelIndexH++) { int inputIndexH = inputIndexOffset.y + kernelIndexH; int inputPosH = inputIndexH + outputIndexN * uConstant.inputSize.y; @@ -51,17 +52,14 @@ void main() vec4 input0 = vec4(0.0f); int inputIndexW0 = inputIndexOffset.x; - int inputPosW0 = (inputIndexW0 < 0 || inputIndexW0 >= uConstant.inputSize.x) ? -1 : inputIndexW0 + outputIndexC4 * uConstant.inputSize.x; - vec4 input1 = texture(uInput, vec2(inputPosW0, inputPosH) / inputImageSize); - + vec4 input1 = (inputIndexW0 >= 0 && inputIndexW0 < uConstant.inputSize.x) ? texelFetch(uInput, ivec2(inputIndexW0 + outputIndexC4 * uConstant.inputSize.x, inputPosH), 0) : vec4(0.0f); for (int kernelIndexW = 0; kernelIndexW < uConstant.kernelSize.x; kernelIndexW++) { // load input input0 = input1; - inputIndexW0 ++; - inputPosW0 = (inputIndexW0 < 0 || inputIndexW0 >= uConstant.inputSize.x) ? -1 : inputIndexW0 + outputIndexC4 * uConstant.inputSize.x; - input1 = texture(uInput, vec2(inputPosW0, inputPosH) / inputImageSize); + inputIndexW0 = inputIndexOffset.x + kernelIndexW + 1; + input1 = (inputIndexW0 >= 0 && inputIndexW0 < uConstant.inputSize.x) ? texelFetch(uInput, ivec2(inputIndexW0 + outputIndexC4 * uConstant.inputSize.x, inputPosH), 0) : vec4(0.0f); // load weight vec4 weight = texelFetch(uKernel, ivec2(kernelIndexW + kernelIndexH * uConstant.kernelSize.x, outputIndexC4), 0); @@ -83,14 +81,12 @@ void main() // write output int outputPosXBase = (outputIndexW2 * 2) + outputIndexC4 * uConstant.outputSize.x; int outputPosY = outputIndexH + outputIndexN * uConstant.outputSize.y; - int WLeft = outputW2 * 2 - uConstant.outputSize.x; - if (outputIndexW2 != (outputW2 - 1) || WLeft == 0) { + if (outputIndexW2 * 2 < uConstant.outputSize.x - 1) { imageStore(uOutput, ivec2(outputPosXBase, outputPosY), result0); imageStore(uOutput, ivec2(outputPosXBase + 1, outputPosY), result1); } else { imageStore(uOutput, ivec2(outputPosXBase, outputPosY), result0); } - } } \ No newline at end of file diff --git a/source/core/Backend.hpp b/source/core/Backend.hpp index d83b2ba10..4a9713b7a 100644 --- a/source/core/Backend.hpp +++ b/source/core/Backend.hpp @@ -29,18 +29,18 @@ struct RuntimeHint { // 0: Defer, 1: Eager int memoryAllocatorType = 0; int winogradMemoryUsed = 3; - + // 0-100, 50 means litter core has 50% capacity of large core int cpuDecreaseRate = 50; int dynamicQuantOption = 0; // 0: Do not quantize - // 1: Only quantize key, use int8 asymmetric quantization + // 1: Only quantize key, use int8 asymmetric quantization // 2: Only quantize value, use fp8 quantization // 3: quantize both key and value // 4: quantize query, key and value, and use gemm int8 kernel to compute K*V int qkvQuantOption = 0; - + // the kvcache size limit of each layer // if the size of kvcache in memory exceeds the limit // it will be moved to disk to save memory @@ -49,10 +49,12 @@ struct RuntimeHint { // path of the kvcache directory std::string kvcacheDirPath = "/tmp"; - + std::string midMemoryPath; std::string weightMemoryPath; - + int mmapFileSize = 1024; // MB + int useCachedMmap = 0; + // op encoder number for once commit int encorderNumForCommit = 10; }; @@ -103,7 +105,9 @@ class Backend : public NonCopyable { - do NOTHING when `onReleaseBuffer` is called. - releases memory when `onClearBuffer` is called or when the backend is deleted. */ - DYNAMIC_SEPERATE + DYNAMIC_SEPERATE, + + DYNAMIC_IN_EXECUTION }; public: @@ -155,7 +159,7 @@ class Backend : public NonCopyable { virtual const Runtime* getRuntime() { return nullptr; } - + /** * @brief allocate buffer of tensor for given storage type. * @param tensor buffer provider. @@ -185,7 +189,7 @@ class Backend : public NonCopyable { * @return MemObj for release, if failed, return nullptr. */ virtual MemObj* onAcquire(const Tensor* tensor, StorageType storageType) = 0; - + virtual bool onSelectDynamicAllocator(int index, int maxIndex) { return false; } @@ -340,6 +344,9 @@ class Runtime : public NonCopyable { MNN_PUBLIC bool hasAsyncWork() const; void setAsyncWork(std::future&& future); MNN_PUBLIC void waitAsyncWork(); + + // TODO: Move to Backend + void* pMeta; private: std::future mFuture; RuntimeHint mHint; diff --git a/source/core/BufferAllocator.cpp b/source/core/BufferAllocator.cpp index 319b707b0..855f3b20d 100644 --- a/source/core/BufferAllocator.cpp +++ b/source/core/BufferAllocator.cpp @@ -67,17 +67,21 @@ class MmapAllocator : public BufferAllocator::Allocator { private: std::map> mCache; std::string mFileName; + std::string mPrefix; std::string mPosfix; int mAllocTimes = 0; bool mRemove; public: - MmapAllocator(const char* dirName, const char* posfix, bool autoRemove) { + MmapAllocator(const char* dirName, const char* prefix, const char* posfix, bool autoRemove) { if (nullptr != dirName) { mFileName = dirName; - if (!MNNDirExist(dirName)) { + if (!MNNCreateDir(dirName)) { MNN_ERROR("%s not exist\n", dirName); } } + if (nullptr != prefix) { + mPrefix = prefix; + } if (nullptr != posfix) { mPosfix = posfix; } @@ -94,10 +98,18 @@ class MmapAllocator : public BufferAllocator::Allocator { } virtual MemChunk onAlloc(size_t size, size_t align) { MNN_ASSERT(size > 0); - std::string fileName = MNNFilePathConcat(mFileName, std::to_string(mAllocTimes) + "." + mPosfix); - auto file = MNNCreateFile(fileName.c_str()); - size = UP_DIV(size, align) * align; - MNNSetFileSize(file, size); + std::string fileName = MNNFilePathConcat(mFileName, mPrefix + std::to_string(mAllocTimes) + "." + mPosfix); + file_t file; + if (MNNFileExist(fileName.c_str())) { + file = MNNOpenFile(fileName.c_str(), MNN_FILE_READ | MNN_FILE_WRITE); + } else { + file = MNNCreateFile(fileName.c_str()); + size = UP_DIV(size, align) * align; + auto code = MNNSetFileSize(file, size); + if (NO_ERROR != code) { + MNN_ERROR("Set File size %lu error= %d\n", size, code); + } + } void* ptr = MNNMmapFile(file, size); mCache.insert(std::make_pair(ptr, std::make_tuple(file, size, fileName))); mAllocTimes++; @@ -117,6 +129,7 @@ class MmapAllocator : public BufferAllocator::Allocator { MNNRemoveFile(std::get<2>(iter->second).c_str()); } mCache.erase(iter); + mAllocTimes = 0; } }; class RecurseAllocator : public BufferAllocator::Allocator { @@ -142,9 +155,9 @@ std::shared_ptr BufferAllocator::Allocator::createDe _res.reset(new DefaultAllocator); return _res; } -std::shared_ptr BufferAllocator::Allocator::createMmap(const char* dirName, const char* posfix, bool autoRemove) { +std::shared_ptr BufferAllocator::Allocator::createMmap(const char* dirName, const char* prefix, const char* posfix, bool autoRemove) { std::shared_ptr _res; - _res.reset(new MmapAllocator(dirName, posfix, autoRemove)); + _res.reset(new MmapAllocator(dirName, prefix, posfix, autoRemove)); return _res; } diff --git a/source/core/BufferAllocator.hpp b/source/core/BufferAllocator.hpp index e4e9f2d42..bcfdfbffb 100644 --- a/source/core/BufferAllocator.hpp +++ b/source/core/BufferAllocator.hpp @@ -85,7 +85,7 @@ class MNN_PUBLIC BufferAllocator : public NonCopyable { virtual MemChunk onAlloc(size_t size, size_t align) = 0; virtual void onRelease(MemChunk chunk) = 0; static std::shared_ptr createDefault(); - static std::shared_ptr createMmap(const char* dirName, const char* posfix, bool autoRemove = true); + static std::shared_ptr createMmap(const char* dirName, const char* prefix, const char* posfix, bool autoRemove = true); static std::shared_ptr createRecurse(BufferAllocator* parent); }; BufferAllocator() = default; diff --git a/source/core/ConvolutionCommon.cpp b/source/core/ConvolutionCommon.cpp index a1890e980..5adbc331e 100644 --- a/source/core/ConvolutionCommon.cpp +++ b/source/core/ConvolutionCommon.cpp @@ -200,6 +200,32 @@ static bool isLinearSample(const std::vector& sample, int bit) { return true; } +static void ReadQuanInfo(BaseLoader* s, size_t* len, ConvolutionCommon::Int8Common* result, bool shapeInt32) { + *len = 1; + // blob shape + unsigned int shape[32] = {0}; + uint32_t shapeDim = (uint32_t)ReadBlobDim(s, shape, 32, shapeInt32); + if (shapeDim == 0 || shapeDim > 32) + return; + for (uint32_t i = 0; i < shapeDim; i++) + *len *= shape[i]; + + // sample + uint32_t sampleCnt = 0; + s->read((char*)&sampleCnt, 1); + if (sampleCnt == 0) { + sampleCnt = 256; + } + result->weightMap.resize(sampleCnt); + auto samples = result->weightMap.data(); + if (samples == nullptr) + return; + s->read((char*)samples, sampleCnt); + SimpleRank(samples, sampleCnt, 1); + uint32_t idxBitsCnt = atLestBitsCnt(sampleCnt); + result->canUseInt4 = idxBitsCnt == 4; +} + static int8_t *ReadQuanData_c(BaseLoader* s, size_t* len, ConvolutionCommon::Int8Common* result, bool shapeInt32, bool forceQuant) { int8_t *blob = nullptr; uint8_t *idxBuf = nullptr; @@ -464,30 +490,41 @@ std::shared_ptr ConvolutionCommon::load(const Op* std::unique_ptr external_buffer; size_t weightLength = 0; int8_t *buffer = nullptr; + bool useCachedMmap = false; + if (backend && backend->getRuntime()) { + useCachedMmap = backend->getRuntime()->hint().useCachedMmap > 1; + } if (USE_EXTERNAL_DATA(conv) && op->externalPath() && quan->buffer() == nullptr) { - // external data auto external_info = conv->external()->data(); + buffer_size = external_info[1]; + alpha_size = external_info[2] / sizeof(float); std::unique_ptr external_file(new FileLoader(op->externalPath()->c_str())); external_file->offset(external_info[0]); - buffer_size = external_info[1]; - if (0 != buffer_size) { - if (1 == quan->type() && !forceFloat) { - buffer = IDSTDecoder::ReadQuanData_c(external_file.get(), &weightLength, result.get(), quan->shapeInt32(), forceInt8); - } else { - external_buffer.reset(new int8_t[buffer_size]); - buffer_ptr = external_buffer.get(); - external_file->read((char*)buffer_ptr, buffer_size); + if (useCachedMmap) { + if (alpha_size) { + result->alpha.reset(alpha_size); + IDSTDecoder::ReadQuanInfo(external_file.get(), &weightLength, result.get(), quan->shapeInt32()); } - } - alpha_size = external_info[2] / sizeof(float); - if (0 != alpha_size) { - result->alpha.reset(alpha_size); - if (nullptr == result->alpha.get()) { - MNN_PRINT("Alloc memory error for extract idst int8\n"); - return nullptr; + } else { + // external data + if (0 != buffer_size) { + if (1 == quan->type() && !forceFloat) { + buffer = IDSTDecoder::ReadQuanData_c(external_file.get(), &weightLength, result.get(), quan->shapeInt32(), forceInt8); + } else { + external_buffer.reset(new int8_t[buffer_size]); + buffer_ptr = external_buffer.get(); + external_file->read((char*)buffer_ptr, buffer_size); + } + } + if (0 != alpha_size) { + result->alpha.reset(alpha_size); + if (nullptr == result->alpha.get()) { + MNN_PRINT("Alloc memory error for extract idst int8\n"); + return nullptr; + } + alpha_ptr = result->alpha.get(); + external_file->read((char*)alpha_ptr, alpha_size * sizeof(float)); } - alpha_ptr = result->alpha.get(); - external_file->read((char*)alpha_ptr, alpha_size * sizeof(float)); } } else { if (quan->buffer()) { @@ -535,6 +572,11 @@ std::shared_ptr ConvolutionCommon::load(const Op* } // read fp16 data if (3 == quan->type()) { + if (useCachedMmap) { + weightLength = buffer_size / sizeof(half_float::half); + result->weightFloat.reset(weightLength); + return result; + } weightLength = buffer_size / sizeof(half_float::half); std::vector tempHalfWeight(buffer_size); ::memcpy(tempHalfWeight.data(), buffer_ptr, buffer_size); @@ -556,24 +598,23 @@ std::shared_ptr ConvolutionCommon::load(const Op* ::memcpy(result->weight.get(), buffer_ptr, weightLength); } - if (result->weight.get() == nullptr) { - if (nullptr == buffer) { - MNN_PRINT("Alloc memory error for extract idst int8\n"); - return nullptr; - } - result->weight.set(buffer, weightLength); + bool oldType4 = (quan->type() == 4 && quan->aMin() == 0 && std::abs(quan->quantScale()) < 1e-6); + if (quan->readType() != 0 || oldType4) { + result->asymmetric = true; + } else { + result->asymmetric = false; } - { - int outputCount = 0; - bool oldType4 = (quan->type() == 4 && quan->aMin() == 0 && std::abs(quan->quantScale()) < 1e-6); - if (quan->readType() != 0 || oldType4) { - result->asymmetric = true; - outputCount = result->alpha.size() / 2; - } else { - result->asymmetric = false; - outputCount = result->alpha.size(); // backward compability with previous symmetric quantization + if (!useCachedMmap) { + if (result->weight.get() == nullptr) { + if (nullptr == buffer) { + MNN_PRINT("Alloc memory error for extract idst int8\n"); + return nullptr; + } + result->weight.set(buffer, weightLength); } + int outputCount = 0; if (result->asymmetric) { + outputCount = result->alpha.size() / 2; // clampMin is minVal in asymmetric quant, clampMin = -(2^(bit)) // and old version clampMin is -128 float clampMin = quan->aMin() == 0 ? -128 : quan->aMin(); @@ -582,6 +623,8 @@ std::shared_ptr ConvolutionCommon::load(const Op* result->alpha.get()[2 * o] = result->alpha.get()[2 * o] - clampMin * result->alpha.get()[2 * o + 1]; } } + } else { + outputCount = result->alpha.size(); // backward compability with previous symmetric quantization } if (!quan->has_scaleInt()) { float extraFactor = quan->quantScale(); diff --git a/source/core/MNNFileUtils.cpp b/source/core/MNNFileUtils.cpp index 445ec2bb3..99abb7748 100644 --- a/source/core/MNNFileUtils.cpp +++ b/source/core/MNNFileUtils.cpp @@ -6,6 +6,7 @@ // Copyright © 2018, Alibaba Group Holding Limited // +#include #include "MNNFileUtils.h" std::string MNNFilePathConcat(std::string prefix, std::string suffix) { @@ -35,6 +36,25 @@ bool MNNFileExist(const char * file_name) #endif } +bool MNNCreateDir(const char * path) { + if (MNNDirExist(path)) { + return true; + } +#if defined(WIN32) || defined(_WIN32) || defined(_WIN64) || defined(_MSC_VER) + if (CreateDirectory(path, NULL) || ERROR_ALREADY_EXISTS == GetLastError()) { + return true; + } else { + return false; + } +#else + if (mkdir(path, 0755) == 0 || errno == EEXIST) { + return true; + } else { + return false; + } +#endif +} + file_t MNNCreateFile(const char * file_name) { #if defined(WIN32) || defined(_WIN32) || defined(_WIN64) || defined(_MSC_VER) @@ -48,7 +68,7 @@ file_t MNNCreateFile(const char * file_name) NULL // No Template ); if (hd == INVALID_HANDLE_VALUE) { - printf("Failed to create the file: %s\n", file_name); + MNN_PRINT("Failed to create the file: %s\n", file_name); return INVALID_FILE; } return hd; @@ -59,7 +79,7 @@ file_t MNNCreateFile(const char * file_name) 0666 // Read and Write Permission for Everyone ); if (fd == -1) { - printf("Failed to create the file: %s\n", file_name); + MNN_PRINT("Failed to create the file: %s\n", file_name); return INVALID_FILE; } return fd; @@ -69,6 +89,7 @@ file_t MNNCreateFile(const char * file_name) file_t MNNOpenFile(const char * file_name, uint32_t flags) { if (!MNNFileExist(file_name)) { + MNN_PRINT("File not exist: %s\n", file_name); return INVALID_FILE; } #if defined(WIN32) || defined(_WIN32) || defined(_WIN64) || defined(_MSC_VER) @@ -89,7 +110,7 @@ file_t MNNOpenFile(const char * file_name, uint32_t flags) NULL // No Template ); if (hd == INVALID_HANDLE_VALUE) { - printf("Failed to open the file: %s\n", file_name); + MNN_PRINT("Failed to open the file: %s\n", file_name); return INVALID_FILE; } return hd; @@ -103,7 +124,7 @@ file_t MNNOpenFile(const char * file_name, uint32_t flags) } int fd = open(file_name, mode); if (fd == -1) { - printf("Failed to open the file: %s\n", file_name); + MNN_PRINT("Failed to open the file: %s\n", file_name); return INVALID_FILE; } return fd; @@ -255,6 +276,7 @@ void * MNNMmapFile(file_t file, size_t size) #if defined(WIN32) || defined(_WIN32) || defined(_WIN64) || defined(_MSC_VER) HANDLE hFileMapping = CreateFileMapping(file, NULL, PAGE_READWRITE, (size >> 32) & 0xffffffff, size & 0xffffffff, NULL); if (hFileMapping == NULL) { + MNN_ERROR("MNN: Mmap failed\n"); return nullptr; } void * addr = MapViewOfFile(hFileMapping, FILE_MAP_READ | FILE_MAP_WRITE, 0, 0, size); @@ -263,6 +285,7 @@ void * MNNMmapFile(file_t file, size_t size) #else void * addr = mmap(NULL, size, PROT_READ | PROT_WRITE, MAP_SHARED, file, 0); if (addr == MAP_FAILED) { + MNN_ERROR("MNN: Mmap failed: %s\n", strerror(errno)); return nullptr; } return addr; @@ -281,4 +304,4 @@ ErrorCode MNNUnmapFile(void * addr, size_t size) } #endif return NO_ERROR; -} \ No newline at end of file +} diff --git a/source/core/MNNFileUtils.h b/source/core/MNNFileUtils.h index a3ecb4be8..cd2267897 100644 --- a/source/core/MNNFileUtils.h +++ b/source/core/MNNFileUtils.h @@ -55,6 +55,14 @@ MNN_PUBLIC std::string MNNFilePathConcat(std::string prefix, std::string suffix) */ MNN_PUBLIC bool MNNDirExist(const char * path); +/*============================================================================================= +** @brief Create a directory if not exists +** @param path -- path of the directory +** @return If the directory exists or create success, returns true +** If the directory does not exist and create fail, return false +*/ +MNN_PUBLIC bool MNNCreateDir(const char * path); + /*============================================================================================= ** @brief Check whether a file exists ** @param file_name -- path of the file @@ -179,4 +187,4 @@ MNN_PUBLIC void * MNNMmapFile(file_t file, size_t size); */ MNN_PUBLIC ErrorCode MNNUnmapFile(void * addr, size_t size); -#endif // MNN_FileUtils_H \ No newline at end of file +#endif // MNN_FileUtils_H diff --git a/source/core/OpCommonUtils.hpp b/source/core/OpCommonUtils.hpp index a51c901d0..407d61035 100644 --- a/source/core/OpCommonUtils.hpp +++ b/source/core/OpCommonUtils.hpp @@ -15,6 +15,28 @@ namespace MNN { struct Op; struct CoreFunctions; +#ifdef MNN_SUPPORT_TRANSFORMER_FUSE +struct KVMeta { + size_t block = 4096; + size_t previous = 0; + size_t remove = 0; + int* reserve = nullptr; + int n_reserve = 0; + size_t add = 0; + int computeReverseSize() const { + int sum = 0; + for (int i=0; iexternal() && param->external()->size() > 1) diff --git a/source/core/Session.cpp b/source/core/Session.cpp index 8f5d21248..3c5cb64e1 100644 --- a/source/core/Session.cpp +++ b/source/core/Session.cpp @@ -99,6 +99,10 @@ void Session::ModeGroup::setHint(Interpreter::HintMode mode, int hint) { break; case Interpreter::OP_ENCODER_NUMBER_FOR_COMMIT: runtimeHint.encorderNumForCommit = hint; + case Interpreter::MMAP_FILE_SIZE: + runtimeHint.mmapFileSize = hint; + case Interpreter::USE_CACHED_MMAP: + runtimeHint.useCachedMmap = hint; default: break; } diff --git a/test/expr/MultiThreadLoad.cpp b/test/expr/MultiThreadLoad.cpp index 85cec3dcb..8b87797e6 100644 --- a/test/expr/MultiThreadLoad.cpp +++ b/test/expr/MultiThreadLoad.cpp @@ -10,6 +10,7 @@ #include #include #include "MNNTestSuite.h" +#include "TestUtils.h" #include "MNN_generated.h" using namespace MNN::Express; using namespace MNN; @@ -34,10 +35,12 @@ class MultiThreadLoadTest : public MNNTestCase { auto bufferOutput = builderOutput.GetBufferPointer(); std::vector threads; + auto forwardType = getCurrentType(); for (int i = 0; i < 100; ++i) { threads.emplace_back([&]() { std::shared_ptr interp(Interpreter::createFromBuffer(bufferOutput, sizeOutput)); ScheduleConfig config; + config.type = forwardType; auto session = interp->createSession(config); interp->runSession(session); }); diff --git a/test/op/AttentionTest.cpp b/test/op/AttentionTest.cpp index 402391952..3dc32799e 100644 --- a/test/op/AttentionTest.cpp +++ b/test/op/AttentionTest.cpp @@ -8,6 +8,7 @@ #ifdef MNN_SUPPORT_TRANSFORMER_FUSE #include #include +#include "core/OpCommonUtils.hpp" #include "MNNTestSuite.h" #include "TestUtils.h" #include @@ -216,6 +217,11 @@ class AttentionTest : public MNNTestCase { virtual bool run(int precision) { srand(2024); + auto rt = ExecutorScope::Current()->getRuntime(); + MNN::KVMeta meta; + for (auto& iter : rt.first) { + iter.second->pMeta = &meta; + } std::shared_ptr naiveAttention(new NaiveAttention); std::shared_ptr attention(new MNN::OpT); attention->type = MNN::OpType_Attention; @@ -223,6 +229,7 @@ class AttentionTest : public MNNTestCase { attention->main.value = new MNN::AttentionParamT; attention->main.AsAttentionParam()->kv_cache = true; int seq_len = 10; + meta.add = seq_len; generateInput(seq_len); generateMask(seq_len, seq_len); expected_result = naiveAttention->onExecute(query, key, value, mask, seq_len); diff --git a/tools/audio/source/audio.cpp b/tools/audio/source/audio.cpp index c91748723..6383582ef 100644 --- a/tools/audio/source/audio.cpp +++ b/tools/audio/source/audio.cpp @@ -24,6 +24,7 @@ #include #endif + namespace MNN { namespace AUDIO { #ifdef _MSC_VER diff --git a/tools/converter/source/optimizer/onnxextra/OnnxScatterND.cpp b/tools/converter/source/optimizer/onnxextra/OnnxScatterND.cpp index cf3b05b68..03ff83513 100644 --- a/tools/converter/source/optimizer/onnxextra/OnnxScatterND.cpp +++ b/tools/converter/source/optimizer/onnxextra/OnnxScatterND.cpp @@ -25,17 +25,24 @@ class OnnxScatterNdTransformer : public OnnxExtraManager::Transform { return nullptr; } // Onnx Scatter = data + MNN::Scatter(indice, update, shape) + auto config = Global::Get(); auto data = inputs[0]; auto info = data->getInfo(); auto type = halide_type_of(); if (nullptr != info) { type = info->type; } + auto shape = _Shape(data, true); auto indice = inputs[1]; auto update = inputs[2]; - auto config = Global::Get(); + if (config->optimizeLevel < 2) { + auto indiceShape = _Shape(indice, true); + auto indiceRank = _Rank(indice); + auto lastDim = _Slice(indiceShape, _Unsqueeze(indiceRank - _Scalar(1), {0}), _Unsqueeze(_Scalar(1), {0})); + auto clipShape = _Slice(shape, _Unsqueeze(_Scalar(0), {0}), lastDim); + indice = _Mod(indice + clipShape, clipShape); + } auto version = config->targetVersion; - auto shape = _Shape(data, true); if (version < 2.0f) { // For target version < 2.0 , don't support 4 input scatternd auto tfRes = _ScatterNd(indice, update, shape); diff --git a/tools/converter/source/optimizer/postconvert/RemoveTestNoUseOps.hpp b/tools/converter/source/optimizer/postconvert/RemoveTestNoUseOps.hpp index ea80c50ee..6919d994d 100644 --- a/tools/converter/source/optimizer/postconvert/RemoveTestNoUseOps.hpp +++ b/tools/converter/source/optimizer/postconvert/RemoveTestNoUseOps.hpp @@ -14,7 +14,6 @@ #include #include "../PostTreatUtils.hpp" #include "MNN/MNNDefine.h" -//#define MNN_USE_ORIGIN_OUTPUT using namespace MNN; class RemoveTestNoUseOps : public PostConverter { @@ -27,14 +26,11 @@ class RemoveTestNoUseOps : public PostConverter { virtual bool shouldDeleteOutput(const MNN::OpT* op) const = 0; virtual bool onExecute(std::unique_ptr& net) const override { - const MNN::NetT* const netPtr = net.get(); -#ifdef MNN_USE_ORIGIN_OUTPUT std::set netOutputNames; for (auto& t : net->outputName) { netOutputNames.insert(t); } -#endif std::unordered_set removedInputs; for (auto iter = net->oplists.begin(); iter != net->oplists.end();) { auto& op = *iter; @@ -43,36 +39,39 @@ class RemoveTestNoUseOps : public PostConverter { iter++; continue; } + bool hasOutputName = false; + for (auto o : op->outputIndexes) { + if (netOutputNames.find(net->tensorName[o]) != netOutputNames.end()) { + hasOutputName = true; + break; + } + } + bool hasOutputFromInput = false; + for (auto o : op->inputIndexes) { + if (netOutputNames.find(net->tensorName[o]) != netOutputNames.end()) { + hasOutputFromInput = true; + break; + } + } + if (hasOutputFromInput && hasOutputName) { + iter++; + continue; + } bool deleteOutput = shouldDeleteOutput(op.get()); // Find the next op if (op->outputIndexes.empty() || op->inputIndexes.empty()) { iter = net->oplists.erase(iter); continue; } - auto originInput = op->inputIndexes[0]; auto originOutputs = op->outputIndexes; -#ifdef MNN_USE_ORIGIN_OUTPUT - if (!deleteOutput) { + if ((!deleteOutput) && hasOutputName) { for (auto o : originOutputs) { if (netOutputNames.find(net->tensorName[o]) != netOutputNames.end()) { net->tensorName[originInput] = net->tensorName[o]; } } } -#else - // If subnet's output is from removed op, use removed op's input name as output name - if (!deleteOutput) { - for (auto idx : originOutputs) { - for (auto& o : net->outputName) { - if (o == net->tensorName[idx]) { - o = net->tensorName[originInput]; - break; - } - } - } - } -#endif for (auto subIter = net->oplists.begin(); subIter != net->oplists.end(); subIter++) { auto& subOp = *subIter; if (deleteOutput) { diff --git a/transformers/llm/engine/CMakeLists.txt b/transformers/llm/engine/CMakeLists.txt index 6fb3b9351..a2557c79b 100644 --- a/transformers/llm/engine/CMakeLists.txt +++ b/transformers/llm/engine/CMakeLists.txt @@ -27,6 +27,7 @@ if (MNN_SEP_BUILD) else() add_library(llm STATIC ${SRCS}) endif() + list(APPEND MNN_DEPS llm) else() add_library(llm OBJECT ${SRCS}) endif() @@ -39,11 +40,10 @@ if (LLM_SUPPORT_AUDIO AND MNN_BUILD_AUDIO) endif() add_executable(llm_demo ${CMAKE_CURRENT_LIST_DIR}/llm_demo.cpp) +target_link_libraries(llm_demo ${MNN_DEPS}) add_executable(embedding_demo ${CMAKE_CURRENT_LIST_DIR}/embedding_demo.cpp) -IF (NOT MNN_SEP_BUILD) - target_link_libraries(llm_demo ${MNN_DEPS}) - target_link_libraries(embedding_demo ${MNN_DEPS}) -ELSE () - target_link_libraries(llm_demo ${MNN_DEPS} llm) - target_link_libraries(embedding_demo ${MNN_DEPS} llm) -ENDIF () +target_link_libraries(embedding_demo ${MNN_DEPS}) +add_executable(audio_demo ${CMAKE_CURRENT_LIST_DIR}/audio_demo.cpp) +target_link_libraries(audio_demo ${MNN_DEPS}) +add_executable(rollback_demo ${CMAKE_CURRENT_LIST_DIR}/rollback_demo.cpp) +target_link_libraries(rollback_demo ${MNN_DEPS}) diff --git a/transformers/llm/engine/audio_demo.cpp b/transformers/llm/engine/audio_demo.cpp new file mode 100644 index 000000000..50a0e1661 --- /dev/null +++ b/transformers/llm/engine/audio_demo.cpp @@ -0,0 +1,162 @@ +// +// llm_demo.cpp +// +// Created by MNN on 2023/03/24. +// ZhaodeWang +// + +#include "llm/llm.hpp" +#define MNN_OPEN_TIME_TRACE +#include +#include +#include +#include +#include +#include + +static void saveVar(MNN::Express::VARP var, std::string name) { + auto ptr = var->readMap(); + auto size = var->getInfo()->size; + std::ofstream os(name.c_str()); + for (int i=0; i> _getInputIdsFromLogits(MNN::Transformer::Llm* llm, MNN::Express::VARP logits, int texSize, int audioSize) { + auto info = logits->getInfo(); + auto basicOffset = info->size - info->dim[2]; + std::vector> decodeIds(8); + decodeIds[7] = {llm->sample(logits, {}, basicOffset, texSize)}; + for (int i=0; i<7; ++i) { + int id = llm->sample(logits, {}, basicOffset + texSize + i * audioSize, audioSize); + id = id + texSize + i * audioSize; + decodeIds[i] = {id}; + } + for (int i=0; i<8; ++i) { + FUNC_PRINT(decodeIds[i][0]); + } + return decodeIds; +} + +int main(int argc, const char* argv[]) { + if (argc < 3) { + std::cout << "Usage: " << argv[0] << " config.json audio.txt" << std::endl; + return 0; + } + MNN::BackendConfig backendConfig; + auto executor = MNN::Express::Executor::newExecutor(MNN_FORWARD_CPU, backendConfig, 1); + MNN::Express::ExecutorScope s(executor); + std::shared_ptr audioEncode(MNN::Express::Module::load({"audio_features"}, {"audio_embed"}, "/Users/xtjiang/alicnn/AliNNPrivate/build/whisper_mlp_fp16.mnn")); + MNN::Express::VARP audio = MNN::Express::_Input({1, 98, 768}, MNN::Express::NCHW, halide_type_of()); + { + std::ifstream is(argv[2]); + auto size = audio->getInfo()->size; + auto ptr = audio->writeMap(); + for (int i=0; i> t; + ptr[i] = t; + } + } +// saveVar(audio, "audio_before.txt"); + audio = audioEncode->onForward({audio})[0]; + int T = audio->getInfo()->dim[1]; + int input_a = 4098, eoa=4096, answer_a=4099, pad_a = 4097; + std::vector> inputIds(8); + for (int i=0; i<7; ++i) { + inputIds[i].resize(T+3); + inputIds[i][0] = layershift(input_a, i); + for (int j=0; j llm(MNN::Transformer::Llm::createLLM(config_path)); + llm->set_config("{\"tmp_path\":\"tmp\"}"); + llm->load(); + llm->generate_init(); + llm->switchMode(MNN::Transformer::Llm::Prefill); + int texSize = 152000; + int audioSize = 4160; + // Prefill + { + MNN::Express::VARP embeddings; + auto audioPtr = audio->readMap(); + auto audioStride = audio->getInfo()->dim[1] * audio->getInfo()->dim[2]; + saveVar(audio, "audio.txt"); + for (int i=0; iembedding(inputIds[i]); + if (i != 7) { + // Replace by audio + auto dstPtr = (float*)embed->readMap() + audio->getInfo()->dim[2] * 1; + ::memcpy(dstPtr, audioPtr, audioStride * sizeof(float)); + } + if (0 == i) { + embeddings = embed; + } else { + embeddings = embeddings + embed; + } + } + embeddings = embeddings * MNN::Express::_Scalar(1.0f/8.0f); + saveVar(embeddings, "embeddings.txt"); + + auto info = embeddings->getInfo(); + auto inputPos = MNN::Express::_Input({1, T+3}, MNN::Express::NCHW, halide_type_of()); + for (int i=0; iwriteMap()[i] = i; + } + auto logits = llm->forwardRaw(embeddings, llm->gen_attention_mask(T+3), inputPos); + { + auto info = logits->getInfo(); + auto basicOffset = info->size - info->dim[2]; + auto ptr = logits->readMap() + basicOffset; + + std::ofstream os("logit.txt"); + for (int i=0; idim[2]; ++i) { + os << ptr[i] << std::endl; + } + } + inputIds = _getInputIdsFromLogits(llm.get(), logits, texSize, audioSize); + } + llm->switchMode(MNN::Transformer::Llm::Decode); + std::vector embeddingsVec(inputIds.size()); + for (int index=0; index<1; ++index) { + MNN::Express::VARP embeddings; + for (int i=0; iembedding(inputIds[i]); + if (0 == i) { + embeddings = emb; + } else { + embeddings = embeddings + emb; + } + } + embeddings = embeddings * MNN::Express::_Scalar(1.0f/8.0f); + auto inputPos = MNN::Express::_Input({1, 1}, MNN::Express::NCHW, halide_type_of()); + inputPos->writeMap()[0] = T+3; + auto logits = llm->forwardRaw(embeddings, llm->gen_attention_mask(1), inputPos); + saveVar(logits, "logit_decode.txt"); + auto size = logits->getInfo()->size; + auto ptr = logits->readMap(); + auto basicOffset = logits->getInfo()->size - logits->getInfo()->dim[2]; + auto texId = llm->sample(logits, {}, basicOffset, texSize); + inputIds = _getInputIdsFromLogits(llm.get(), logits, texSize, audioSize); + FUNC_PRINT_ALL(llm->tokenizer_decode(inputIds[7][0]).c_str(), s); + } + + return 0; +} diff --git a/transformers/llm/engine/include/llm/llm.hpp b/transformers/llm/engine/include/llm/llm.hpp index f8b45788a..0cab96469 100644 --- a/transformers/llm/engine/include/llm/llm.hpp +++ b/transformers/llm/engine/include/llm/llm.hpp @@ -34,11 +34,31 @@ enum TuneType { // op encoder number for commit OP_ENCODER_NUMBER = 0, }; - +struct KVMeta; class MNN_PUBLIC Llm { using PromptItem = std::pair; // public: - Llm(std::shared_ptr config) : config_(config) {} + enum Stage { + Prefill, + Decode + }; + struct GenerateState { + // forward info + int prompt_len_ = 0; + int gen_seq_len_ = 0; + int all_seq_len_ = 0; + std::vector history_ids_; + // time + int64_t vision_us_ = 0; + int64_t audio_us_ = 0; + int64_t prefill_us_ = 0; + int64_t decode_us_ = 0; + int current_token_ = 0; + std::vector output_ids_; + std::ostream* os_ = nullptr; + std::string end_with_; + }; + Llm(std::shared_ptr config); virtual ~Llm(); static Llm* createLLM(const std::string& config_path); void chat(); @@ -46,15 +66,23 @@ class MNN_PUBLIC Llm { void trace(bool start); void tuning(TuneType type, std::vector candidates); virtual void load(); + void switchMode(Stage stage); + MNN::Express::VARP forwardRaw(MNN::Express::VARP hiddenState, MNN::Express::VARP mask, MNN::Express::VARP inputPos); + virtual MNN::Express::VARP gen_attention_mask(int seq_len); + virtual MNN::Express::VARP embedding(const std::vector& input_ids); + MNN::Express::VARP forward(const std::vector& input_ids); - int sample(MNN::Express::VARP logits, const std::vector& pre_ids); + int sample(MNN::Express::VARP logits, const std::vector& pre_ids, int offset = 0, int size = 0); std::string apply_prompt_template(const std::string& user_content) const; std::string apply_chat_template(const std::vector& chat_prompts) const; - std::string response(const std::string& user_content, std::ostream* os = &std::cout, const char* end_with = nullptr); - std::string response(const std::vector& chat_prompts, std::ostream* os = &std::cout, const char* end_with = nullptr); - void generate_init(); - std::string generate(const std::vector& input_ids, std::ostream* os, const char* end_with); + size_t getCurrentHistory() const; + void eraseHistory(size_t begin, size_t end); + void response(const std::string& user_content, std::ostream* os = &std::cout, const char* end_with = nullptr, int max_new_tokens = -1); + void response(const std::vector& chat_prompts, std::ostream* os = &std::cout, const char* end_with = nullptr, int max_new_tokens = -1); + void generate_init(std::ostream* os = nullptr, const char* end_with = nullptr); + void generate(int max_token); std::vector generate(const std::vector& input_ids, int max_new_tokens = -1); + bool stoped(); void print_speed(); // config function std::string dump_config(); @@ -69,25 +97,14 @@ class MNN_PUBLIC Llm { std::string tokenizer_decode(int id); virtual std::vector tokenizer_encode(const std::string& query, bool use_template = true); friend class Pipeline; -public: - // forward info - int prompt_len_ = 0; - int gen_seq_len_ = 0; - int all_seq_len_ = 0; - std::vector history_ids_; - // time - int64_t vision_us_ = 0; - int64_t audio_us_ = 0; - int64_t prefill_us_ = 0; - int64_t decode_us_ = 0; - bool is_single_ = true; - bool attention_fused_ = true; + const GenerateState& getState() const { + return mState; + } protected: + std::shared_ptr mMeta; std::shared_ptr config_; std::shared_ptr tokenizer_; std::shared_ptr disk_embedding_; - std::vector key_value_shape_ = {}; - std::vector past_key_values_; MNN::Express::VARP inputs_embeds_, attention_mask_, position_ids_; std::shared_ptr runtime_manager_; std::shared_ptr mllm_runtime_manager_; @@ -95,10 +112,9 @@ class MNN_PUBLIC Llm { std::vector> prefill_modules_, decode_modules_, current_modules_; const MNN::Express::Module* base_module_ = nullptr; void init_runtime(); - virtual MNN::Express::VARP embedding(const std::vector& input_ids); - virtual MNN::Express::VARP gen_attention_mask(int seq_len); virtual MNN::Express::VARP gen_position_ids(int seq_len); bool mTracing = false; + GenerateState mState; }; // Embedding start diff --git a/transformers/llm/engine/ios/mnn-llm/mnn-llm.xcodeproj/project.pbxproj b/transformers/llm/engine/ios/mnn-llm/mnn-llm.xcodeproj/project.pbxproj index 7672178ca..9af67bf26 100644 --- a/transformers/llm/engine/ios/mnn-llm/mnn-llm.xcodeproj/project.pbxproj +++ b/transformers/llm/engine/ios/mnn-llm/mnn-llm.xcodeproj/project.pbxproj @@ -14,7 +14,6 @@ 4D5B97C42B2B29CF003AF2F1 /* LLMInferenceEngineWrapper.mm in Sources */ = {isa = PBXBuildFile; fileRef = 4D5B97C32B2B29CF003AF2F1 /* LLMInferenceEngineWrapper.mm */; }; CE1A4A5D2C8596D900A62A4F /* MNN.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = CE1A4A5C2C8596D900A62A4F /* MNN.framework */; }; CE1A4A7C2C85B69800A62A4F /* config.json in Resources */ = {isa = PBXBuildFile; fileRef = CE1A4A722C85B69800A62A4F /* config.json */; }; - CE1A4A7D2C85B69800A62A4F /* embeddings_bf16.bin in Resources */ = {isa = PBXBuildFile; fileRef = CE1A4A732C85B69800A62A4F /* embeddings_bf16.bin */; }; CE1A4A7E2C85B69800A62A4F /* llm_config.json in Resources */ = {isa = PBXBuildFile; fileRef = CE1A4A742C85B69800A62A4F /* llm_config.json */; }; CE1A4A7F2C85B69800A62A4F /* llm.mnn in Resources */ = {isa = PBXBuildFile; fileRef = CE1A4A752C85B69800A62A4F /* llm.mnn */; }; CE1A4A802C85B69800A62A4F /* llm.mnn.weight in Resources */ = {isa = PBXBuildFile; fileRef = CE1A4A762C85B69800A62A4F /* llm.mnn.weight */; }; @@ -46,7 +45,6 @@ 4D5B97C32B2B29CF003AF2F1 /* LLMInferenceEngineWrapper.mm */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.objcpp; path = LLMInferenceEngineWrapper.mm; sourceTree = ""; }; CE1A4A5C2C8596D900A62A4F /* MNN.framework */ = {isa = PBXFileReference; lastKnownFileType = wrapper.framework; name = MNN.framework; path = ../MNN.framework; sourceTree = ""; }; CE1A4A722C85B69800A62A4F /* config.json */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = text.json; path = config.json; sourceTree = ""; }; - CE1A4A732C85B69800A62A4F /* embeddings_bf16.bin */ = {isa = PBXFileReference; lastKnownFileType = archive.macbinary; path = embeddings_bf16.bin; sourceTree = ""; }; CE1A4A742C85B69800A62A4F /* llm_config.json */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = text.json; path = llm_config.json; sourceTree = ""; }; CE1A4A752C85B69800A62A4F /* llm.mnn */ = {isa = PBXFileReference; lastKnownFileType = file; path = llm.mnn; sourceTree = ""; }; CE1A4A762C85B69800A62A4F /* llm.mnn.weight */ = {isa = PBXFileReference; lastKnownFileType = file; path = llm.mnn.weight; sourceTree = ""; }; @@ -119,7 +117,6 @@ children = ( CE1A4A852C85D43E00A62A4F /* bench.txt */, CE1A4A722C85B69800A62A4F /* config.json */, - CE1A4A732C85B69800A62A4F /* embeddings_bf16.bin */, CE1A4A742C85B69800A62A4F /* llm_config.json */, CE1A4A752C85B69800A62A4F /* llm.mnn */, CE1A4A762C85B69800A62A4F /* llm.mnn.weight */, @@ -196,7 +193,6 @@ CE1A4A7E2C85B69800A62A4F /* llm_config.json in Resources */, CE1A4A802C85B69800A62A4F /* llm.mnn.weight in Resources */, CE1A4A7F2C85B69800A62A4F /* llm.mnn in Resources */, - CE1A4A7D2C85B69800A62A4F /* embeddings_bf16.bin in Resources */, CE1A4A7C2C85B69800A62A4F /* config.json in Resources */, ); runOnlyForDeploymentPostprocessing = 0; diff --git a/transformers/llm/engine/ios/mnn-llm/mnn-llm/LLMInferenceEngineWrapper.mm b/transformers/llm/engine/ios/mnn-llm/mnn-llm/LLMInferenceEngineWrapper.mm index 4561338f8..50acc3e67 100644 --- a/transformers/llm/engine/ios/mnn-llm/mnn-llm/LLMInferenceEngineWrapper.mm +++ b/transformers/llm/engine/ios/mnn-llm/mnn-llm/LLMInferenceEngineWrapper.mm @@ -93,12 +93,13 @@ - (void)processInput:(NSString *)input withStreamHandler:(StreamOutputHandler)ha int decode_len = 0; int64_t prefill_time = 0; int64_t decode_time = 0; + auto status = llm->getState(); for (int i = 0; i < prompts.size(); i++) { llm->response(prompts[i], &os, "\n"); - prompt_len += llm->prompt_len_; - decode_len += llm->gen_seq_len_; - prefill_time += llm->prefill_us_; - decode_time += llm->decode_us_; + prompt_len += status.prompt_len_; + decode_len += status.gen_seq_len_; + prefill_time += status.prefill_us_; + decode_time += status.decode_us_; } float prefill_s = prefill_time / 1e6; float decode_s = decode_time / 1e6; diff --git a/transformers/llm/engine/llm_demo.cpp b/transformers/llm/engine/llm_demo.cpp index 8083cf881..66f19ea9e 100644 --- a/transformers/llm/engine/llm_demo.cpp +++ b/transformers/llm/engine/llm_demo.cpp @@ -14,15 +14,6 @@ #include using namespace MNN::Transformer; -static void trace_prepare(Llm* llm) { - MNN_PRINT("Prepare for resize opt Begin\n"); - llm->trace(true); - std::ostringstream cacheOs; - llm->generate({200, 200}, &cacheOs, ""); - MNN_PRINT("Prepare for resize opt End\n"); - llm->trace(false); -} - static void tuning_prepare(Llm* llm) { MNN_PRINT("Prepare for tuning opt Begin\n"); llm->tuning(OP_ENCODER_NUMBER, {1, 5, 10, 20, 30, 50, 100}); @@ -72,7 +63,7 @@ std::vector> parse_csv(const std::vector& return csv_data; } -static int benchmark(Llm* llm, const std::vector& prompts) { +static int benchmark(Llm* llm, const std::vector& prompts, int max_token_number) { int prompt_len = 0; int decode_len = 0; int64_t vision_time = 0; @@ -80,19 +71,30 @@ static int benchmark(Llm* llm, const std::vector& prompts) { int64_t prefill_time = 0; int64_t decode_time = 0; // llm->warmup(); + auto& state = llm->getState(); + if (max_token_number > 0) { + llm->set_config("{\"max_new_tokens\":1}"); + } for (int i = 0; i < prompts.size(); i++) { const auto& prompt = prompts[i]; // prompt start with '#' will be ignored if (prompt.substr(0, 1) == "#") { continue; } - llm->response(prompt); - prompt_len += llm->prompt_len_; - decode_len += llm->gen_seq_len_; - vision_time += llm->vision_us_; - audio_time += llm->audio_us_; - prefill_time += llm->prefill_us_; - decode_time += llm->decode_us_; + if (max_token_number > 0) { + llm->response(prompt, &std::cout, nullptr, 0); + while (!llm->stoped() && state.gen_seq_len_ < max_token_number) { + llm->generate(1); + } + } else { + llm->response(prompt); + } + prompt_len += state.prompt_len_; + decode_len += state.gen_seq_len_; + vision_time += state.vision_us_; + audio_time += state.audio_us_; + prefill_time += state.prefill_us_; + decode_time += state.decode_us_; } float vision_s = vision_time / 1e6; float audio_s = audio_time / 1e6; @@ -125,8 +127,11 @@ static int ceval(Llm* llm, const std::vector& lines, std::string fi prompt += "\n\n"; printf("%s", prompt.c_str()); printf("## 进度: %d / %lu\n", i, lines.size() - 1); - auto res = llm->response(prompt.c_str()); - answers.push_back(res); + std::ostringstream lineOs; + llm->response(prompt.c_str(), &lineOs); + auto line = lineOs.str(); + printf("%s", line.c_str()); + answers.push_back(line); } { auto position = filename.rfind("/"); @@ -149,7 +154,7 @@ static int ceval(Llm* llm, const std::vector& lines, std::string fi return 0; } -static int eval(Llm* llm, std::string prompt_file) { +static int eval(Llm* llm, std::string prompt_file, int max_token_number) { std::cout << "prompt file is " << prompt_file << std::endl; std::ifstream prompt_fs(prompt_file); std::vector prompts; @@ -168,7 +173,7 @@ static int eval(Llm* llm, std::string prompt_file) { if (prompts[0] == "id,question,A,B,C,D,answer") { return ceval(llm, prompts, prompt_file); } - return benchmark(llm, prompts); + return benchmark(llm, prompts, max_token_number); } int main(int argc, const char* argv[]) { @@ -188,10 +193,6 @@ int main(int argc, const char* argv[]) { AUTOTIME; llm->load(); } - if (true) { - AUTOTIME; - trace_prepare(llm.get()); - } if (true) { AUTOTIME; tuning_prepare(llm.get()); @@ -200,6 +201,11 @@ int main(int argc, const char* argv[]) { llm->chat(); return 0; } + int max_token_number = -1; + if (argc >= 4) { + std::istringstream os(argv[3]); + os >> max_token_number; + } std::string prompt_file = argv[2]; - return eval(llm.get(), prompt_file); + return eval(llm.get(), prompt_file, max_token_number); } diff --git a/transformers/llm/engine/rollback_demo.cpp b/transformers/llm/engine/rollback_demo.cpp new file mode 100644 index 000000000..bb7a5b7e5 --- /dev/null +++ b/transformers/llm/engine/rollback_demo.cpp @@ -0,0 +1,155 @@ +// +// llm_demo.cpp +// +// Created by MNN on 2023/03/24. +// ZhaodeWang +// + +#include "llm/llm.hpp" +#define MNN_OPEN_TIME_TRACE +#include +#include +#include +#include +#include +using namespace MNN::Transformer; + + +std::vector> parse_csv(const std::vector& lines) { + std::vector> csv_data; + std::string line; + std::vector row; + std::string cell; + bool insideQuotes = false; + bool startCollecting = false; + + // content to stream + std::string content = ""; + for (auto line : lines) { + content = content + line + "\n"; + } + std::istringstream stream(content); + + while (stream.peek() != EOF) { + char c = stream.get(); + if (c == '"') { + if (insideQuotes && stream.peek() == '"') { // quote + cell += '"'; + stream.get(); // skip quote + } else { + insideQuotes = !insideQuotes; // start or end text in quote + } + startCollecting = true; + } else if (c == ',' && !insideQuotes) { // end element, start new element + row.push_back(cell); + cell.clear(); + startCollecting = false; + } else if ((c == '\n' || stream.peek() == EOF) && !insideQuotes) { // end line + row.push_back(cell); + csv_data.push_back(row); + cell.clear(); + row.clear(); + startCollecting = false; + } else { + cell += c; + startCollecting = true; + } + } + return csv_data; +} + +static int benchmark(Llm* llm, const std::vector& prompts, int max_token_number) { + if (prompts.size() < 3) { + MNN_ERROR("Need larger than 3 inputs\n"); + return 0; + } + auto& state = llm->getState(); + int initSize = 2; + if (max_token_number <= 0) { + max_token_number = 512; + } + MNN_PRINT("Prefill\n"); + std::vector history; + for (int i = 0; i < 3; i++) { + const auto& prompt = prompts[i]; + llm->response(prompt, &std::cout, nullptr, 0); + history.emplace_back(llm->getCurrentHistory()); + } + MNN_PRINT("\n"); + + MNN_PRINT("[LLM Test: Erase 1]\n"); + llm->eraseHistory(history[0], history[1]); + llm->response(prompts[prompts.size()-1], &std::cout, nullptr, 0); + while (!llm->stoped() && state.gen_seq_len_ < max_token_number) { + llm->generate(1); + } + MNN_PRINT("\n[LLM Test End]\n"); + + llm->eraseHistory(0, 0); + history.clear(); + for (int i = 0; i < 3; i++) { + const auto& prompt = prompts[i]; + llm->response(prompt, &std::cout, nullptr, 0); + history.emplace_back(llm->getCurrentHistory()); + } + MNN_PRINT("[LLM Test: Erase 2]\n"); + llm->eraseHistory(history[1], history[2]); + llm->response(prompts[prompts.size()-1], &std::cout, nullptr, 0); + while (!llm->stoped() && state.gen_seq_len_ < max_token_number) { + llm->generate(1); + } + MNN_PRINT("\n[LLM Test End]\n"); + MNN_PRINT("[LLM Test For Init]\n"); + llm->reset(); + llm->eraseHistory(0, 0); + llm->response(prompts[prompts.size()-1], &std::cout, nullptr, 0); + while (!llm->stoped() && state.gen_seq_len_ < max_token_number) { + llm->generate(1); + } + MNN_PRINT("\n[LLM Test End]\n"); + return 0; +} + +static int eval(Llm* llm, std::string prompt_file, int max_token_number) { + std::cout << "prompt file is " << prompt_file << std::endl; + std::ifstream prompt_fs(prompt_file); + std::vector prompts; + std::string prompt; + while (std::getline(prompt_fs, prompt)) { + if (prompt.back() == '\r') { + prompt.pop_back(); + } + prompts.push_back(prompt); + } + prompt_fs.close(); + if (prompts.empty()) { + return 1; + } + return benchmark(llm, prompts, max_token_number); +} + +int main(int argc, const char* argv[]) { + if (argc < 2) { + std::cout << "Usage: " << argv[0] << " config.json " << std::endl; + return 0; + } + MNN::BackendConfig backendConfig; + auto executor = MNN::Express::Executor::newExecutor(MNN_FORWARD_CPU, backendConfig, 1); + MNN::Express::ExecutorScope s(executor); + + std::string config_path = argv[1]; + std::cout << "config path is " << config_path << std::endl; + std::unique_ptr llm(Llm::createLLM(config_path)); + llm->set_config("{\"tmp_path\":\"tmp\"}"); + { + AUTOTIME; + llm->load(); + } + int max_token_number = -1; + if (argc >= 4) { + std::istringstream os(argv[3]); + os >> max_token_number; + } + std::string prompt_file = argv[2]; + return eval(llm.get(), prompt_file, max_token_number); +} diff --git a/transformers/llm/engine/src/llm.cpp b/transformers/llm/engine/src/llm.cpp index e7f1e3474..293e1af1b 100644 --- a/transformers/llm/engine/src/llm.cpp +++ b/transformers/llm/engine/src/llm.cpp @@ -18,7 +18,7 @@ #include "llm/llm.hpp" #include "llmconfig.hpp" #include "tokenizer.hpp" -// 0: no debug, 1: test op time, 2: print tensor info +// 0: no debug, 1: test op time, 2: print tensor info, 3: print tensor in output #define DEBUG_MODE 0 #include "httplib.h" @@ -32,7 +32,26 @@ using namespace MNN::Express; namespace MNN { namespace Transformer { - +struct KVMeta { + size_t block = 4096; + size_t previous = 0; + size_t remove = 0; + int* reserve = nullptr; + int n_reserve = 0; + size_t add = 0; + std::vector reserveHost; + void sync() { + int revertNumber = 0; + for (int i=0; iconfig_.merge(content.c_str()); } +int file_size_m(const std::string& filename) { + std::ifstream file(filename, std::ios::binary | std::ios::ate); + if (!file.is_open()) { + std::cerr << "Could not open the file!" << std::endl; + return -1; + } + long long fileSize = file.tellg(); + file.close(); + return fileSize / (1024 * 1024); +} + void Llm::init_runtime() { ScheduleConfig config; BackendConfig cpuBackendConfig; @@ -230,6 +260,8 @@ void Llm::init_runtime() { runtime_manager_->setHint(MNN::Interpreter::DYNAMIC_QUANT_OPTIONS, 1); // 1: per batch quant, 2: per tensor quant runtime_manager_->setHint(MNN::Interpreter::QKV_QUANT_OPTIONS, config_->quant_qkv()); runtime_manager_->setHint(MNN::Interpreter::KVCACHE_SIZE_LIMIT, config_->kvcache_limit()); + runtime_manager_->setHint(MNN::Interpreter::MMAP_FILE_SIZE, file_size_m(config_->llm_weight()) + 128); + runtime_manager_->setHint(MNN::Interpreter::USE_CACHED_MMAP, 1); std::string tmpPath = config_->tmp_path(); if (config_->kvcache_mmap()) { runtime_manager_->setExternalPath(tmpPath, MNN::Interpreter::EXTERNAL_PATH_KVCACHE_DIR); @@ -237,6 +269,7 @@ void Llm::init_runtime() { if (config_->use_mmap()) { runtime_manager_->setExternalPath(tmpPath, MNN::Interpreter::EXTERNAL_WEIGHT_DIR); } + runtime_manager_->setHintPtr(Interpreter::KVCACHE_INFO, mMeta.get()); #if DEBUG_MODE == 1 runtime_manager_->setMode(MNN::Interpreter::Session_Debug); @@ -245,6 +278,10 @@ void Llm::init_runtime() { #if DEBUG_MODE == 2 runtime_manager_->setMode(MNN::Interpreter::Session_Debug); _initTensorStatic(); +#endif +#if DEBUG_MODE == 3 + runtime_manager_->setMode(MNN::Interpreter::Session_Debug); + _initDebug(); #endif { std::string cacheFilePath = tmpPath.length() != 0 ? tmpPath : "."; @@ -255,10 +292,6 @@ void Llm::init_runtime() { void Llm::load() { init_runtime(); // init module status - key_value_shape_ = config_->key_value_shape(); - is_single_ = config_->is_single(); - attention_fused_ = config_->attention_fused(); - MNN_PRINT("### is_single_ = %d\n", is_single_); // 1. load vocab MNN_PRINT("load tokenizer\n"); tokenizer_.reset(Tokenizer::createTokenizer(config_->tokenizer_file())); @@ -266,32 +299,26 @@ void Llm::load() { disk_embedding_.reset(new DiskEmbedding(config_)); // 3. load model Module::Config module_config; - module_config.shapeMutable = true; + if (config_->backend_type() == "opencl" || config_->backend_type() == "vulkan") { + module_config.shapeMutable = false; + } else { + module_config.shapeMutable = true; + } module_config.rearrange = true; // using base module for lora module if (base_module_ != nullptr) { module_config.base = base_module_; } int layer_nums = config_->layer_nums(); - if (is_single_) { - // load single model - key_value_shape_.insert(key_value_shape_.begin(), layer_nums); - modules_.resize(1); - std::string model_path = config_->llm_model(); - MNN_PRINT("load %s ... ", model_path.c_str()); - runtime_manager_->setExternalFile(config_->llm_weight()); - if (attention_fused_) { - modules_[0].reset(Module::load({"input_ids", "attention_mask", "position_ids"}, {"logits"}, - model_path.c_str(), runtime_manager_, &module_config)); - } else { - modules_[0].reset(Module::load({"input_ids", "attention_mask", "position_ids", "past_key_values"}, - {"logits", "presents"}, model_path.c_str(), runtime_manager_, - &module_config)); - } - MNN_PRINT("Load Module Done!\n"); - } else { - MNN_ERROR("Split version is depercerate\n"); - } + // load single model + modules_.resize(1); + std::string model_path = config_->llm_model(); + MNN_PRINT("load %s ... ", model_path.c_str()); + runtime_manager_->setExternalFile(config_->llm_weight()); + modules_[0].reset(Module::load( + {"input_ids", "attention_mask", "position_ids"}, + {"logits"}, model_path.c_str(), runtime_manager_, &module_config)); + MNN_PRINT("Load Module Done!\n"); decode_modules_.resize(modules_.size()); for (int v = 0; v < modules_.size(); ++v) { decode_modules_[v].reset(Module::clone(modules_[v].get())); @@ -308,14 +335,8 @@ size_t Llm::apply_lora(const std::string& lora_path) { module_config.rearrange = true; module_config.base = modules_.begin()->get(); size_t lora_index = modules_.size(); - if (attention_fused_) { - modules_.emplace_back(Module::load({"input_ids", "attention_mask", "position_ids"}, {"logits"}, + modules_.emplace_back(Module::load({"input_ids", "attention_mask", "position_ids"}, {"logits"}, model_path.c_str(), runtime_manager_, &module_config)); - } else { - modules_.emplace_back(Module::load({"input_ids", "attention_mask", "position_ids", "past_key_values"}, - {"logits", "presents"}, model_path.c_str(), runtime_manager_, - &module_config)); - } select_module(lora_index); return lora_index; } @@ -404,41 +425,47 @@ void Llm::tuning(TuneType type, std::vector candidates) { } runtime_manager_->setHint(MNN::Interpreter::OP_ENCODER_NUMBER_FOR_COMMIT, prefer_candidate); } +void Llm::switchMode(Llm::Stage stage) { + switch (stage) { + case Prefill: + current_modules_ = prefill_modules_; + break; + case Decode: + current_modules_ = decode_modules_; + break; + default: + break; + } +} -VARP Llm::forward(const std::vector& input_ids) { - int seq_len = input_ids.size(); - auto attention_mask = gen_attention_mask(seq_len); - auto position_ids = gen_position_ids(seq_len); +MNN::Express::VARP Llm::forwardRaw(MNN::Express::VARP hiddenState, MNN::Express::VARP mask, MNN::Express::VARP inputPos) { VARP logits; - if (is_single_) { - std::vector outputs; - auto hidden_states = embedding(input_ids); - if (attention_fused_) { - outputs = current_modules_.back()->onForward({hidden_states, attention_mask, position_ids}); - } else { - outputs = - current_modules_.back()->onForward({hidden_states, attention_mask, position_ids, past_key_values_[0]}); - } - if (outputs.empty()) { - return nullptr; - } - logits = outputs[0]; - if (!attention_fused_) { - past_key_values_[0] = outputs[1]; - } - } else { - MNN_ERROR("Split models is depercarate\n"); + std::vector outputs; + outputs = current_modules_.back()->onForward({hiddenState, mask, inputPos}); + if (outputs.empty()) { return nullptr; } - all_seq_len_ += seq_len; - gen_seq_len_++; + logits = outputs[0]; + return logits; +} + +VARP Llm::forward(const std::vector& input_ids) { + int seq_len = input_ids.size(); + auto attention_mask = gen_attention_mask(seq_len); + auto position_ids = gen_position_ids(seq_len); + auto hidden_states = embedding(input_ids); + auto logits = forwardRaw(hidden_states, attention_mask, position_ids); + mState.all_seq_len_ += seq_len; + mState.gen_seq_len_++; return logits; } -int Llm::sample(VARP logits, const std::vector& pre_ids) { +int Llm::sample(VARP logits, const std::vector& pre_ids, int offset, int size) { std::unordered_set ids_set(pre_ids.begin(), pre_ids.end()); - auto scores = (float*)(logits->readMap()); - auto size = logits->getInfo()->size; + auto scores = (float*)(logits->readMap()) + offset; + if (0 == size) { + size = logits->getInfo()->size; + } // repetition penalty const float repetition_penalty = 1.1; for (auto id : ids_set) { @@ -446,9 +473,9 @@ int Llm::sample(VARP logits, const std::vector& pre_ids) { scores[id] = score < 0 ? score * repetition_penalty : score / repetition_penalty; } // argmax - float max_score = 0; - int token_id = 0; - for (int i = 0; i < size; i++) { + float max_score = scores[0]; + int token_id = 0; + for (int i = 1; i < size; i++) { float score = scores[i]; if (score > max_score) { max_score = score; @@ -517,125 +544,129 @@ void Llm::chat() { response(user_str); } else { history.emplace_back(std::make_pair("user", user_str)); - auto assistant_str = response(history); - history.emplace_back(std::make_pair("assistant", assistant_str)); + std::ostringstream lineOs; + response(history, &lineOs, nullptr, 1); + auto line = lineOs.str(); + while (!stoped() && mState.gen_seq_len_ < config_->max_new_tokens()) { + std::cout << line << std::flush; + lineOs.str(""); + generate(1); + line = lineOs.str(); + } + history.emplace_back(std::make_pair("assistant", line)); } std::cout << std::endl; } } void Llm::reset() { - history_ids_.clear(); - all_seq_len_ = 0; + mState.history_ids_.clear(); + mState.all_seq_len_ = 0; } -void Llm::generate_init() { +void Llm::generate_init(std::ostream* os, const char* end_with) { // init status - gen_seq_len_ = 0; - vision_us_ = 0; - audio_us_ = 0; - prefill_us_ = 0; - decode_us_ = 0; - past_key_values_.clear(); - if (is_single_) { - past_key_values_.push_back(_Input(key_value_shape_, NCHW)); - } else { - for (int i = 0; i < config_->layer_nums(); i++) { - past_key_values_.push_back(_Input(key_value_shape_, NCHW)); - } - } + mState.os_ = os; + if (nullptr != end_with) { + mState.end_with_ = end_with; + } + mState.gen_seq_len_ = 0; + mState.vision_us_ = 0; + mState.audio_us_ = 0; + mState.prefill_us_ = 0; + mState.decode_us_ = 0; + mState.current_token_ = 0; if (!config_->reuse_kv()) { - all_seq_len_ = 0; - history_ids_.clear(); + mState.all_seq_len_ = 0; + mState.history_ids_.clear(); + mMeta->remove = mMeta->previous; } + mState.output_ids_.clear(); current_modules_ = prefill_modules_; } - -std::vector Llm::generate(const std::vector& input_ids, int max_new_tokens) { - generate_init(); - std::vector output_ids, all_ids = input_ids; - prompt_len_ = static_cast(input_ids.size()); - if (max_new_tokens < 0) { - max_new_tokens = config_->max_new_tokens(); +size_t Llm::getCurrentHistory() const { + return mMeta->previous; +} +void Llm::eraseHistory(size_t begin, size_t end) { + if (0 == end) { + end = mMeta->previous; } - // prefill - current_modules_ = prefill_modules_; - auto logits = forward(input_ids); - if (logits.get() == nullptr) { - return {}; + if (end > mMeta->previous || begin >= end) { + MNN_ERROR("Invalid erase range history larger than current\n"); + return; } - int token = sample(logits, all_ids); - output_ids.push_back(token); - all_ids.push_back(token); - // decode - current_modules_ = decode_modules_; - while (gen_seq_len_ < max_new_tokens) { - logits = nullptr; - logits = forward({token}); - if (logits.get() == nullptr) { - return {}; + if (mMeta->remove != 0) { + MNN_ERROR("MNN-LLM: erase history hasn't been executed by response, override erase info\n"); + } + mMeta->remove = mMeta->previous - begin; + if (end != mMeta->previous) { + mMeta->reserveHost.resize(2); + mMeta->reserve = mMeta->reserveHost.data(); + mMeta->n_reserve = 1; + mMeta->reserve[0] = end - begin; + mMeta->reserve[1] = mMeta->previous - end; + } +} + +bool Llm::stoped() { + return is_stop(mState.current_token_); +} + +void Llm::generate(int max_token) { + int len = 0; + while (len < max_token) { + auto st = std::chrono::system_clock::now(); + if (nullptr != mState.os_) { + *mState.os_ << tokenizer_decode(mState.current_token_); + *mState.os_ << std::flush; + } + mState.history_ids_.push_back(mState.current_token_); + mMeta->add = 1; + mMeta->remove = 0; + auto logits = forward({mState.current_token_}); + mMeta->sync(); + len++; + if (nullptr == logits.get()) { + break; + } + if (logits->getInfo()->size == 0) { + break; } - token = sample(logits, all_ids); - if (is_stop(token)) { + mState.current_token_ = sample(logits, mState.history_ids_); + auto et = std::chrono::system_clock::now(); + mState.decode_us_ += std::chrono::duration_cast(et - st).count(); + if (is_stop(mState.current_token_) && nullptr != mState.os_) { + *mState.os_ << mState.end_with_ << std::flush; break; } - output_ids.push_back(token); - all_ids.push_back(token); } - return output_ids; } -std::string Llm::generate(const std::vector& input_ids, std::ostream* os, const char* end_with) { - if (mTracing) { - // Skip real forward - current_modules_ = prefill_modules_; - forward(input_ids); - current_modules_ = decode_modules_; - forward({input_ids[0]}); - forward({input_ids[0]}); - return "Test"; +std::vector Llm::generate(const std::vector& input_ids, int max_tokens) { + if (max_tokens < 0) { + max_tokens = config_->max_new_tokens(); } - prompt_len_ = static_cast(input_ids.size()); - history_ids_.insert(history_ids_.end(), input_ids.begin(), input_ids.end()); // push to history_ids_ + mMeta->add = input_ids.size(); + mState.prompt_len_ = static_cast(input_ids.size()); + mState.history_ids_.insert(mState.history_ids_.end(), input_ids.begin(), input_ids.end()); // push to history_ids_ auto st = std::chrono::system_clock::now(); current_modules_ = prefill_modules_; auto logits = forward(input_ids); if (nullptr == logits.get()) { - return ""; - } - int token = sample(logits, history_ids_); - auto et = std::chrono::system_clock::now(); - current_modules_ = decode_modules_; - std::string output_str = tokenizer_decode(token); - prefill_us_ = std::chrono::duration_cast(et - st).count(); - *os << output_str << std::flush; - while (gen_seq_len_ < config_->max_new_tokens()) { - st = std::chrono::system_clock::now(); - history_ids_.push_back(token); - logits = nullptr; - logits = forward({token}); - if (nullptr == logits.get()) { - return ""; - } - if (logits->getInfo()->size == 0) { - return ""; - } - token = sample(logits, history_ids_); - et = std::chrono::system_clock::now(); - decode_us_ += std::chrono::duration_cast(et - st).count(); - if (is_stop(token)) { - *os << end_with << std::flush; - break; - } - auto word = tokenizer_decode(token); - *os << word << std::flush; - output_str += word; + return {}; } - ExecutorScope::Current()->gc(Executor::FULL); + mState.current_token_ = sample(logits, mState.history_ids_); + logits = nullptr; + auto et = std::chrono::system_clock::now(); + current_modules_ = decode_modules_; + mState.prefill_us_ = std::chrono::duration_cast(et - st).count(); + mMeta->sync(); + generate(max_tokens); + #ifdef DUMP_PROFILE_INFO print_speed(); #endif - return output_str; + return mState.output_ids_; } std::vector Llm::tokenizer_encode(const std::string& user_content, bool use_template) { @@ -647,40 +678,26 @@ std::vector Llm::tokenizer_encode(const std::string& user_content, bool use return input_ids; } -std::string Llm::response(const std::string& user_content, std::ostream* os, const char* end_with) { - generate_init(); +void Llm::response(const std::string& user_content, std::ostream* os, const char* end_with, int max_new_tokens) { if (!end_with) { end_with = "\n"; } + generate_init(os, end_with); std::vector input_ids; - if (config_->reuse_kv()) { - auto prompt = apply_prompt_template(user_content); - if (all_seq_len_ > 0) { - prompt = "<|im_end|>\n" + prompt; - } - input_ids = tokenizer_->encode(prompt); - } else { - input_ids = tokenizer_encode(user_content); - } - return generate(input_ids, os, end_with); + input_ids = tokenizer_encode(user_content); + generate(input_ids, max_new_tokens); } -std::string Llm::response(const std::vector& chat_prompts, std::ostream* os, const char* end_with) { +void Llm::response(const std::vector& chat_prompts, std::ostream* os, const char* end_with, int max_new_tokens) { if (chat_prompts.empty()) { - return ""; - } - generate_init(); - if (!end_with) { - end_with = "\n"; + return; } auto prompt = apply_chat_template(chat_prompts); - if (config_->reuse_kv() && all_seq_len_ > 0) { - prompt = "<|im_end|>\n" + prompt; - } - // std::cout << "# prompt : " << prompt << std::endl; - auto input_ids = tokenizer_->encode(prompt); - // printf("input_ids (%lu): ", input_ids.size()); for (auto id : input_ids) printf("%d, ", id); printf("\n"); - return generate(input_ids, os, end_with); + response(prompt, os, end_with, max_new_tokens); +} + +Llm::Llm(std::shared_ptr config) : config_(config) { + mMeta.reset(new KVMeta); } Llm::~Llm() { @@ -716,28 +733,28 @@ Llm::~Llm() { } void Llm::print_speed() { - auto vision_s = vision_us_ * 1e-6; - auto audio_s = audio_us_ * 1e-6; - auto prefill_s = prefill_us_ * 1e-6; - auto decode_s = decode_us_ * 1e-6; + auto vision_s = mState.vision_us_ * 1e-6; + auto audio_s = mState.audio_us_ * 1e-6; + auto prefill_s = mState.prefill_us_ * 1e-6; + auto decode_s = mState.decode_us_ * 1e-6; auto total_s = vision_s + audio_s + prefill_s + decode_s; printf("\n#################################\n"); - printf(" total tokens num = %d\n", prompt_len_ + gen_seq_len_); - printf("prompt tokens num = %d\n", prompt_len_); - printf("output tokens num = %d\n", gen_seq_len_); + printf(" total tokens num = %d\n", mState.prompt_len_ + mState.gen_seq_len_); + printf("prompt tokens num = %d\n", mState.prompt_len_); + printf("output tokens num = %d\n", mState.gen_seq_len_); printf(" total time = %.2f s\n", total_s); if (1 || vision_s) { printf(" vision time = %.2f s\n", audio_s); } - if (1 || audio_us_) { + if (1 || audio_s) { printf(" audio time = %.2f s\n", audio_s); } printf("prefill time = %.2f s\n", prefill_s); printf(" decode time = %.2f s\n", decode_s); - printf(" total speed = %.2f tok/s\n", (prompt_len_ + gen_seq_len_) / total_s); - printf("prefill speed = %.2f tok/s\n", prompt_len_ / prefill_s); - printf(" decode speed = %.2f tok/s\n", gen_seq_len_ / decode_s); - printf(" chat speed = %.2f tok/s\n", gen_seq_len_ / total_s); + printf(" total speed = %.2f tok/s\n", (mState.prompt_len_ + mState.gen_seq_len_) / total_s); + printf("prefill speed = %.2f tok/s\n", mState.prompt_len_ / prefill_s); + printf(" decode speed = %.2f tok/s\n", mState.gen_seq_len_ / decode_s); + printf(" chat speed = %.2f tok/s\n", mState.gen_seq_len_ / total_s); printf("##################################\n"); } @@ -754,13 +771,11 @@ static inline bool needNewVar(VARP var, int axis, int seq_len) { VARP Llm::embedding(const std::vector& input_ids) { AUTOTIME; int hidden_size = config_->hidden_size(); - int seq_len = static_cast(input_ids.size()); - if (needNewVar(inputs_embeds_, 0, seq_len)) { - inputs_embeds_ = _Input({seq_len, 1, hidden_size}, NCHW); - } + int seq_len = static_cast(input_ids.size()); + VARP res = _Input({seq_len, 1, hidden_size}, NCHW); // disk embedding to save memory - disk_embedding_->embedding(input_ids, inputs_embeds_->writeMap()); - return inputs_embeds_; + disk_embedding_->embedding(input_ids, res->writeMap()); + return res; } std::string Llm::tokenizer_decode(int id) { @@ -774,7 +789,7 @@ std::string Llm::tokenizer_decode(int id) { } VARP Llm::gen_attention_mask(int seq_len) { - int kv_seq_len = all_seq_len_ + seq_len; + int kv_seq_len = mState.all_seq_len_ + seq_len; if (seq_len == 1) { kv_seq_len = seq_len; } @@ -787,7 +802,7 @@ VARP Llm::gen_attention_mask(int seq_len) { auto ptr = attention_mask_->writeMap(); for (int i = 0; i < seq_len; i++) { for (int j = 0; j < kv_seq_len; j++) { - int row = i + all_seq_len_; + int row = i + mState.all_seq_len_; ptr[kv_seq_len * i + j] = (j > row) * std::numeric_limits::lowest(); } } @@ -813,7 +828,7 @@ VARP Llm::gen_attention_mask(int seq_len) { bool is_glm2 = config_->attention_mask() == "glm2"; for (int i = 0; i < seq_len; i++) { for (int j = 0; j < kv_seq_len; j++) { - int row = i + all_seq_len_; + int row = i + mState.all_seq_len_; ptr[seq_len * i + j] = is_glm2 ? j > row : j <= row; } } @@ -830,8 +845,8 @@ VARP Llm::gen_position_ids(int seq_len) { } auto ptr = position_ids_->writeMap(); if (seq_len == 1) { - ptr[0] = all_seq_len_ - gen_seq_len_ - 2; - ptr[1] = gen_seq_len_ + 1; + ptr[0] = mState.all_seq_len_ - mState.gen_seq_len_ - 2; + ptr[1] = mState.gen_seq_len_ + 1; } else { for (int i = 0; i < seq_len - 1; i++) { ptr[i] = i; @@ -848,10 +863,10 @@ VARP Llm::gen_position_ids(int seq_len) { } auto ptr = position_ids_->writeMap(); if (seq_len == 1) { - ptr[0] = is_glm2 ? gen_seq_len_ : all_seq_len_; + ptr[0] = is_glm2 ? mState.gen_seq_len_ : mState.all_seq_len_; } else { for (int i = 0; i < seq_len; i++) { - ptr[i] = i + all_seq_len_; + ptr[i] = i + mState.all_seq_len_; } } return position_ids_;