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#0: remove device arg from maxpool2d
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@mywoodstock
mywoodstock committed Oct 10, 2024
1 parent 015296d commit 554363d
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Showing 14 changed files with 4 additions and 68 deletions.
2 changes: 0 additions & 2 deletions models/demos/convnet_mnist/tt/convnet_mnist.py
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Expand Up @@ -74,7 +74,6 @@ def convnet_mnist(
stride=[1, 1],
padding=[0, 0],
dilation=[1, 1],
device=device,
)

[x, out_height, out_width, weights_device, bias_device] = ttnn.conv2d(
Expand Down Expand Up @@ -118,7 +117,6 @@ def convnet_mnist(
stride=[1, 1],
padding=[0, 0],
dilation=[1, 1],
device=device,
)
x = ttnn.from_device(x)
x = ttnn.reshape(x, (x.shape[0], -1))
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2 changes: 0 additions & 2 deletions models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_large_new_conv_api.py
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Expand Up @@ -560,7 +560,6 @@ def first_run(self, input_tensor, device, batch_size, ops_parallel_config) -> tt
stride=[2, 2],
padding=[1, 1],
dilation=[1, 1],
device=device,
)

x_height = 128
Expand Down Expand Up @@ -867,7 +866,6 @@ def optimized_run(self, input_tensor, device, batch_size, ops_parallel_config, c
stride=[2, 2],
padding=[1, 1],
dilation=[1, 1],
device=device,
)

x_height = 128
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1 change: 0 additions & 1 deletion models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_new_conv_api.py
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Expand Up @@ -746,7 +746,6 @@ def run(self, input_tensor, device, ops_parallel_config, conv_op_cache={}) -> tt
stride=[2, 2],
padding=[1, 1],
dilation=[1, 1],
device=device,
)

x_height = 56
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2 changes: 0 additions & 2 deletions models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_xlarge_new_conv_api.py
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Expand Up @@ -557,7 +557,6 @@ def first_run(self, input_tensor, device, batch_size, ops_parallel_config) -> tt
stride=[2, 2],
padding=[1, 1],
dilation=[1, 1],
device=device,
)

x_height = 224
Expand Down Expand Up @@ -861,7 +860,6 @@ def optimized_run(self, input_tensor, device, batch_size, ops_parallel_config, c
stride=[2, 2],
padding=[1, 1],
dilation=[1, 1],
device=device,
)

x_height = 224
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2 changes: 0 additions & 2 deletions models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_xlarge_new_conv_api_24.py
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Expand Up @@ -559,7 +559,6 @@ def first_run(self, input_tensor, device, batch_size, ops_parallel_config) -> tt
stride=[2, 2],
padding=[1, 1],
dilation=[1, 1],
device=device,
)

x_height = 224
Expand Down Expand Up @@ -891,7 +890,6 @@ def optimized_run(self, input_tensor, device, batch_size, ops_parallel_config, c
stride=[2, 2],
padding=[1, 1],
dilation=[1, 1],
device=device,
)

x_height = 224
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2 changes: 0 additions & 2 deletions models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_xxlarge_new_conv_api.py
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Expand Up @@ -631,7 +631,6 @@ def first_run(self, input_tensor, device, batch_size, ops_parallel_config) -> tt
stride=[2, 2],
padding=[1, 1],
dilation=[1, 1],
device=device,
)

x_height = 256
Expand Down Expand Up @@ -965,7 +964,6 @@ def optimized_run(self, input_tensor, device, batch_size, ops_parallel_config, c
stride=[2, 2],
padding=[1, 1],
dilation=[1, 1],
device=device,
)

x_height = 256
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2 changes: 0 additions & 2 deletions models/demos/vgg/tt/ttnn_vgg.py
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Expand Up @@ -78,7 +78,6 @@ def ttnn_vgg16(
stride=[2, 2],
padding=[0, 0],
dilation=[1, 1],
device=device,
)
ttnn.deallocate(ttact_d)
tt_x = ttnn.from_device(tt_x)
Expand Down Expand Up @@ -206,7 +205,6 @@ def ttnn_vgg11(
stride=[2, 2],
padding=[0, 0],
dilation=[1, 1],
device=device,
)
tt_x = ttnn.from_device(tt_x)
ttnn.deallocate(ttact_d)
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1 change: 0 additions & 1 deletion models/experimental/functional_unet/tt/unet_shallow_ttnn.py
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Expand Up @@ -232,7 +232,6 @@ def __call__(self, x):
stride=[self.pool.stride, self.pool.stride],
padding=[self.pool.padding, self.pool.padding],
dilation=[self.pool.dilation, self.pool.dilation],
device=self.device,
)
return x

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3 changes: 0 additions & 3 deletions models/experimental/yolov4/ttnn/neck.py
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Original file line number Diff line number Diff line change
Expand Up @@ -191,7 +191,6 @@ def __call__(self, device, input_tensor):
stride=[1, 1],
padding=[2, 2],
dilation=[1, 1],
device=device,
)
pool_2 = ttnn.max_pool2d(
input_tensor=output_tensor,
Expand All @@ -203,7 +202,6 @@ def __call__(self, device, input_tensor):
stride=[1, 1],
padding=[4, 4],
dilation=[1, 1],
device=device,
)
pool_3 = ttnn.max_pool2d(
input_tensor=output_tensor,
Expand All @@ -215,7 +213,6 @@ def __call__(self, device, input_tensor):
stride=[1, 1],
padding=[6, 6],
dilation=[1, 1],
device=device,
)

pool_1 = ttnn.sharded_to_interleaved(pool_1, ttnn.L1_MEMORY_CONFIG)
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1 change: 0 additions & 1 deletion tests/ttnn/sweep_tests/sweeps/sweeps/max_pool2d.py
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Expand Up @@ -95,7 +95,6 @@ def run(
stride=[stride_h, stride_w],
padding=[pad_h, pad_w],
dilation=[dilation_h, dilation_w],
device=device,
)
out_padded = out_d.cpu()
out_pytorch_padded = ttnn.to_torch(out_padded)
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2 changes: 0 additions & 2 deletions tests/ttnn/unit_tests/operations/test_maxpool2d.py
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Original file line number Diff line number Diff line change
Expand Up @@ -107,7 +107,6 @@ def run_max_pool(
stride=[stride_h, stride_w],
padding=[pad_h, pad_w],
dilation=[dilation_h, dilation_w],
device=device,
)

# interleaved_mem_config = ttnn.L1_MEMORY_CONFIG
Expand Down Expand Up @@ -477,7 +476,6 @@ def test_pool_core_nondivis(
stride=[stride_h, stride_w],
padding=[pad_h, pad_w],
dilation=[dilation_h, dilation_w],
device=device,
)

# interleaved_mem_config = ttnn.L1_MEMORY_CONFIG
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9 changes: 2 additions & 7 deletions ttnn/cpp/ttnn/operations/pool/maxpool/max_pool2d.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -12,8 +12,7 @@
namespace ttnn {
namespace operations::pool {

template<typename T>
Tensor MaxPool2DOp::invoke(uint8_t queue_id, const Tensor& input_tensor, uint32_t batch_size, uint32_t input_h, uint32_t input_w, uint32_t channels, std::array<uint32_t, 2> kernel_size, std::array<uint32_t, 2> stride, std::array<uint32_t, 2> padding, std::array<uint32_t, 2> dilation, T* device) {
Tensor MaxPool2DOp::invoke(uint8_t queue_id, const Tensor& input_tensor, uint32_t batch_size, uint32_t input_h, uint32_t input_w, uint32_t channels, std::array<uint32_t, 2> kernel_size, std::array<uint32_t, 2> stride, std::array<uint32_t, 2> padding, std::array<uint32_t, 2> dilation) {

sliding_window::SlidingWindowConfig sliding_window_config{
.batch_size = batch_size,
Expand Down Expand Up @@ -43,7 +42,7 @@ Tensor MaxPool2DOp::invoke(uint8_t queue_id, const Tensor& input_tensor, uint32_
output_shape[1],
output_shape[2],
0, // out_channels -- not used
device,
input_tensor.device(),
ShardOrientation::ROW_MAJOR,
false);
num_cores_nhw = conv::conv2d::get_num_cores_nhw_from_parallel_config(parallel_config);
Expand Down Expand Up @@ -104,9 +103,5 @@ Tensor MaxPool2DOp::invoke(uint8_t queue_id, const Tensor& input_tensor, uint32_
memory_config);
}

// device template specializations
template Tensor MaxPool2DOp::invoke<Device>(uint8_t queue_id, const Tensor& input_tensor, uint32_t batch_size, uint32_t input_h, uint32_t input_w, uint32_t channels, std::array<uint32_t, 2> kernel_size, std::array<uint32_t, 2> stride, std::array<uint32_t, 2> padding, std::array<uint32_t, 2> dilation, Device* device);
template Tensor MaxPool2DOp::invoke<MeshDevice>(uint8_t queue_id, const Tensor& input_tensor, uint32_t batch_size, uint32_t input_h, uint32_t input_w, uint32_t channels, std::array<uint32_t, 2> kernel_size, std::array<uint32_t, 2> stride, std::array<uint32_t, 2> padding, std::array<uint32_t, 2> dilation, MeshDevice* device);

} // namespace operations::pool
} // namespace ttnn
3 changes: 1 addition & 2 deletions ttnn/cpp/ttnn/operations/pool/maxpool/max_pool2d.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -16,8 +16,7 @@ namespace ttnn {
namespace operations::pool {

struct MaxPool2DOp {
template<typename T>
static Tensor invoke(uint8_t queue_id, const Tensor& input_tensor, uint32_t batch_size, uint32_t input_h, uint32_t input_w, uint32_t channels, std::array<uint32_t, 2> kernel_size, std::array<uint32_t, 2> stride, std::array<uint32_t, 2> padding, std::array<uint32_t, 2> dilation, T* device);
static Tensor invoke(uint8_t queue_id, const Tensor& input_tensor, uint32_t batch_size, uint32_t input_h, uint32_t input_w, uint32_t channels, std::array<uint32_t, 2> kernel_size, std::array<uint32_t, 2> stride, std::array<uint32_t, 2> padding, std::array<uint32_t, 2> dilation);

};

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40 changes: 1 addition & 39 deletions ttnn/cpp/ttnn/operations/pool/maxpool/max_pool2d_pybind.cpp
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Expand Up @@ -48,7 +48,6 @@ void bind_max_pool2d_operation(py::module& module) {
std::array<uint32_t, 2> stride,
std::array<uint32_t, 2> padding,
std::array<uint32_t, 2> dilation,
ttnn::Device* device,
const uint8_t& queue_id)
-> ttnn::Tensor { return self(queue_id,
input_tensor,
Expand All @@ -59,8 +58,7 @@ void bind_max_pool2d_operation(py::module& module) {
kernel_size,
stride,
padding,
dilation,
device); },
dilation); },
py::arg("input_tensor"),
py::arg("batch_size"),
py::arg("input_h"),
Expand All @@ -71,42 +69,6 @@ void bind_max_pool2d_operation(py::module& module) {
py::arg("padding"),
py::arg("dilation"),
py::kw_only(),
py::arg("device"),
py::arg("queue_id") = 0},
ttnn::pybind_overload_t{
[](const decltype(ttnn::max_pool2d)& self, const ttnn::Tensor& input_tensor,
uint32_t batch_size,
uint32_t input_h,
uint32_t input_w,
uint32_t channels,
std::array<uint32_t, 2> kernel_size,
std::array<uint32_t, 2> stride,
std::array<uint32_t, 2> padding,
std::array<uint32_t, 2> dilation,
MeshDevice* device,
const uint8_t& queue_id)
-> ttnn::Tensor { return self(queue_id,
input_tensor,
batch_size,
input_h,
input_w,
channels,
kernel_size,
stride,
padding,
dilation,
device); },
py::arg("input_tensor"),
py::arg("batch_size"),
py::arg("input_h"),
py::arg("input_w"),
py::arg("channels"),
py::arg("kernel_size"),
py::arg("stride"),
py::arg("padding"),
py::arg("dilation"),
py::kw_only(),
py::arg("device"),
py::arg("queue_id") = 0});
}

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