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Merge branch 'master' of https://github.com/NVIDIA/TRTorch into input…
…_type Signed-off-by: Naren Dasan <[email protected]>
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| Original file line number | Diff line number | Diff line change |
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| #include "cuda_runtime.h" | ||
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| #include "core/runtime/runtime.h" | ||
| #include "core/util/prelude.h" | ||
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| namespace trtorch { | ||
| namespace core { | ||
| namespace runtime { | ||
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| const std::string DEVICE_INFO_DELIM = "%"; | ||
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| typedef enum { ID_IDX = 0, SM_MAJOR_IDX, SM_MINOR_IDX, DEVICE_TYPE_IDX, DEVICE_NAME_IDX } SerializedDeviceInfoIndex; | ||
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| CudaDevice::CudaDevice() : id{-1}, major{-1}, minor{-1}, device_type{nvinfer1::DeviceType::kGPU} {} | ||
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| CudaDevice::CudaDevice(int64_t gpu_id, nvinfer1::DeviceType device_type) { | ||
| CudaDevice cuda_device; | ||
| cudaDeviceProp device_prop; | ||
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| // Device ID | ||
| this->id = gpu_id; | ||
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| // Get Device Properties | ||
| cudaGetDeviceProperties(&device_prop, gpu_id); | ||
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| // Compute capability major version | ||
| this->major = device_prop.major; | ||
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| // Compute capability minor version | ||
| this->minor = device_prop.minor; | ||
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| std::string device_name(device_prop.name); | ||
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| // Set Device name | ||
| this->device_name = device_name; | ||
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| // Set Device Type | ||
| this->device_type = device_type; | ||
| } | ||
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| // NOTE: Serialization Format for Device Info: | ||
| // id%major%minor%(enum)device_type%device_name | ||
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| CudaDevice::CudaDevice(std::string device_info) { | ||
| LOG_DEBUG("Deserializing Device Info: " << device_info); | ||
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| std::vector<std::string> tokens; | ||
| int64_t start = 0; | ||
| int64_t end = device_info.find(DEVICE_INFO_DELIM); | ||
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| while (end != -1) { | ||
| tokens.push_back(device_info.substr(start, end - start)); | ||
| start = end + DEVICE_INFO_DELIM.size(); | ||
| end = device_info.find(DEVICE_INFO_DELIM, start); | ||
| } | ||
| tokens.push_back(device_info.substr(start, end - start)); | ||
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| TRTORCH_CHECK(tokens.size() == DEVICE_NAME_IDX + 1, "Unable to deserializable program target device infomation"); | ||
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| id = std::stoi(tokens[ID_IDX]); | ||
| major = std::stoi(tokens[SM_MAJOR_IDX]); | ||
| minor = std::stoi(tokens[SM_MINOR_IDX]); | ||
| device_type = (nvinfer1::DeviceType)(std::stoi(tokens[DEVICE_TYPE_IDX])); | ||
| device_name = tokens[DEVICE_NAME_IDX]; | ||
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| LOG_DEBUG("Deserialized Device Info: " << *this); | ||
| } | ||
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| std::string CudaDevice::serialize() { | ||
| std::vector<std::string> content; | ||
| content.resize(DEVICE_NAME_IDX + 1); | ||
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| content[ID_IDX] = std::to_string(id); | ||
| content[SM_MAJOR_IDX] = std::to_string(major); | ||
| content[SM_MINOR_IDX] = std::to_string(minor); | ||
| content[DEVICE_TYPE_IDX] = std::to_string((int64_t)device_type); | ||
| content[DEVICE_NAME_IDX] = device_name; | ||
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| std::stringstream ss; | ||
| for (size_t i = 0; i < content.size() - 1; i++) { | ||
| ss << content[i] << DEVICE_INFO_DELIM; | ||
| } | ||
| ss << content[DEVICE_NAME_IDX]; | ||
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| std::string serialized_device_info = ss.str(); | ||
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| LOG_DEBUG("Serialized Device Info: " << serialized_device_info); | ||
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| return serialized_device_info; | ||
| } | ||
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| std::string CudaDevice::getSMCapability() const { | ||
| std::stringstream ss; | ||
| ss << major << "." << minor; | ||
| return ss.str(); | ||
| } | ||
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| std::ostream& operator<<(std::ostream& os, const CudaDevice& device) { | ||
| os << "Device(ID: " << device.id << ", Name: " << device.device_name << ", SM Capability: " << device.major << '.' | ||
| << device.minor << ", Type: " << device.device_type << ')'; | ||
| return os; | ||
| } | ||
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| } // namespace runtime | ||
| } // namespace core | ||
| } // namespace trtorch |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,48 @@ | ||
| #include "cuda_runtime.h" | ||
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| #include "core/runtime/runtime.h" | ||
| #include "core/util/prelude.h" | ||
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| namespace trtorch { | ||
| namespace core { | ||
| namespace runtime { | ||
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| DeviceList::DeviceList() { | ||
| int num_devices = 0; | ||
| auto status = cudaGetDeviceCount(&num_devices); | ||
| if (status != cudaSuccess) { | ||
| LOG_WARNING("Unable to read CUDA capable devices. Return status: " << status); | ||
| } | ||
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| for (int i = 0; i < num_devices; i++) { | ||
| device_list[i] = CudaDevice(i, nvinfer1::DeviceType::kGPU); | ||
| } | ||
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| // REVIEW: DO WE CARE ABOUT DLA? | ||
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| LOG_DEBUG("Runtime:\n Available CUDA Devices: \n" << this->dump_list()); | ||
| } | ||
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| void DeviceList::insert(int device_id, CudaDevice cuda_device) { | ||
| device_list[device_id] = cuda_device; | ||
| } | ||
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| CudaDevice DeviceList::find(int device_id) { | ||
| return device_list[device_id]; | ||
| } | ||
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| DeviceList::DeviceMap DeviceList::get_devices() { | ||
| return device_list; | ||
| } | ||
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| std::string DeviceList::dump_list() { | ||
| std::stringstream ss; | ||
| for (auto it = device_list.begin(); it != device_list.end(); ++it) { | ||
| ss << " " << it->second << std::endl; | ||
| } | ||
| return ss.str(); | ||
| } | ||
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| } // namespace runtime | ||
| } // namespace core | ||
| } // namespace trtorch |
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