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copy found_inf to cpu in advance to improve performance (PaddlePaddle…
…#34274) * copy found_inf to cpu in advance to improve performance * add npu test * add npu test * refine code * refine memcpy op * fix adam
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/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | ||
Licensed under the Apache License, Version 2.0 (the "License"); | ||
you may not use this file except in compliance with the License. | ||
You may obtain a copy of the License at | ||
http://www.apache.org/licenses/LICENSE-2.0 | ||
Unless required by applicable law or agreed to in writing, software | ||
distributed under the License is distributed on an "AS IS" BASIS, | ||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
See the License for the specific language governing permissions and | ||
limitations under the License. */ | ||
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#include <memory> | ||
#include <string> | ||
#include "paddle/fluid/framework/op_registry.h" | ||
#include "paddle/fluid/framework/op_version_registry.h" | ||
#include "paddle/fluid/operators/npu_op_runner.h" | ||
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namespace paddle { | ||
namespace operators { | ||
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template <typename DeviceContext, typename T> | ||
class MatMulNPUKernel : public framework::OpKernel<T> { | ||
public: | ||
void Compute(const framework::ExecutionContext& ctx) const override { | ||
auto* x = ctx.Input<framework::Tensor>("X"); | ||
auto* y = ctx.Input<framework::Tensor>("Y"); | ||
auto* out = ctx.Output<framework::Tensor>("Out"); | ||
bool transpose_x = ctx.Attr<bool>("transpose_X"); | ||
bool transpose_y = ctx.Attr<bool>("transpose_Y"); | ||
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if (x->dims().size() == 2) { | ||
out->mutable_data<T>(ctx.GetPlace()); | ||
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const auto& runner = NpuOpRunner( | ||
"MatMul", {*x, *y}, {*out}, | ||
{{"transpose_x1", transpose_x}, {"transpose_x2", transpose_y}}); | ||
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auto stream = | ||
ctx.template device_context<paddle::platform::NPUDeviceContext>() | ||
.stream(); | ||
runner.Run(stream); | ||
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} else if (x->dims().size() > 2) { | ||
out->mutable_data<T>(ctx.GetPlace()); | ||
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const auto& runner = | ||
NpuOpRunner("BatchMatMul", {*x, *y}, {*out}, | ||
{{"adj_x1", transpose_x}, {"adj_x2", transpose_y}}); | ||
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auto stream = | ||
ctx.template device_context<paddle::platform::NPUDeviceContext>() | ||
.stream(); | ||
runner.Run(stream); | ||
} | ||
} | ||
}; | ||
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template <typename DeviceContext, typename T> | ||
class MatMulGradNPUKernel : public framework::OpKernel<T> { | ||
public: | ||
void Compute(const framework::ExecutionContext& ctx) const override { | ||
auto* x = ctx.Input<framework::Tensor>("X"); | ||
auto* y = ctx.Input<framework::Tensor>("Y"); | ||
auto* dout = ctx.Input<framework::Tensor>(framework::GradVarName("Out")); | ||
auto* dx = ctx.Output<framework::Tensor>(framework::GradVarName("X")); | ||
auto* dy = ctx.Output<framework::Tensor>(framework::GradVarName("Y")); | ||
bool transpose_y = ctx.Attr<bool>("transpose_Y"); | ||
auto stream = | ||
ctx.template device_context<paddle::platform::NPUDeviceContext>() | ||
.stream(); | ||
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if (x->dims().size() == 2) { | ||
if (transpose_y) { | ||
if (dx) { | ||
dx->mutable_data<T>(ctx.GetPlace()); | ||
const auto& runner_dx = | ||
NpuOpRunner("MatMul", {*dout, *y}, {*dx}, | ||
{{"transpose_x1", false}, {"transpose_x2", false}}); | ||
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runner_dx.Run(stream); | ||
} | ||
if (dy) { | ||
dy->mutable_data<T>(ctx.GetPlace()); | ||
const auto& runner_dy = | ||
NpuOpRunner("MatMul", {*dout, *x}, {*dy}, | ||
{{"transpose_x1", true}, {"transpose_x2", false}}); | ||
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runner_dy.Run(stream); | ||
} | ||
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} else { | ||
if (dx) { | ||
dx->mutable_data<T>(ctx.GetPlace()); | ||
const auto& runner_dx = | ||
NpuOpRunner("MatMul", {*dout, *y}, {*dx}, | ||
{{"transpose_x1", false}, {"transpose_x2", true}}); | ||
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runner_dx.Run(stream); | ||
} | ||
if (dy) { | ||
dy->mutable_data<T>(ctx.GetPlace()); | ||
const auto& runner_dy = | ||
NpuOpRunner("MatMul", {*x, *dout}, {*dy}, | ||
{{"transpose_x1", true}, {"transpose_x2", false}}); | ||
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runner_dy.Run(stream); | ||
} | ||
} | ||
} else if (x->dims().size() > 2) { | ||
if (transpose_y) { | ||
if (dx) { | ||
dx->mutable_data<T>(ctx.GetPlace()); | ||
const auto& runner_dx = | ||
NpuOpRunner("BatchMatMul", {*dout, *y}, {*dx}, | ||
{{"adj_x1", false}, {"adj_x2", false}}); | ||
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runner_dx.Run(stream); | ||
} | ||
if (dy) { | ||
dy->mutable_data<T>(ctx.GetPlace()); | ||
const auto& runner_dy = | ||
NpuOpRunner("BatchMatMul", {*dout, *x}, {*dy}, | ||
{{"adj_x1", true}, {"adj_x2", false}}); | ||
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runner_dy.Run(stream); | ||
} | ||
} else { | ||
if (dx) { | ||
dx->mutable_data<T>(ctx.GetPlace()); | ||
const auto& runner_dx = | ||
NpuOpRunner("BatchMatMul", {*dout, *y}, {*dx}, | ||
{{"adj_x1", false}, {"adj_x2", true}}); | ||
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runner_dx.Run(stream); | ||
} | ||
if (dy) { | ||
dy->mutable_data<T>(ctx.GetPlace()); | ||
if ((x->dims().size() == 3) && (dout->dims().size() == 3) && | ||
(dy->dims().size() == 2)) { | ||
framework::Tensor dout_; | ||
dout_.ShareDataWith(*dout); | ||
std::vector<int> vec_dim = framework::vectorize<int>(dout_.dims()); | ||
std::vector<int> vec_dim_v{vec_dim[0] * vec_dim[1], vec_dim[2]}; | ||
dout_.Resize(framework::make_ddim(vec_dim_v)); | ||
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framework::Tensor x_; | ||
x_.ShareDataWith(*x); | ||
std::vector<int> vec_dim_x = framework::vectorize<int>(x_.dims()); | ||
std::vector<int> vec_dim_x_v{vec_dim_x[0] * vec_dim_x[1], | ||
vec_dim_x[2]}; | ||
x_.Resize(framework::make_ddim(vec_dim_x_v)); | ||
const auto& runner_dy = | ||
NpuOpRunner("MatMul", {x_, dout_}, {*dy}, | ||
{{"transpose_x1", true}, {"transpose_x2", false}}); | ||
runner_dy.Run(stream); | ||
} else { | ||
const auto& runner_dy = | ||
NpuOpRunner("BatchMatMul", {*x, *dout}, {*dy}, | ||
{{"adj_x1", true}, {"adj_x2", false}}); | ||
runner_dy.Run(stream); | ||
} | ||
} | ||
} | ||
} | ||
} | ||
}; | ||
} // namespace operators | ||
} // namespace paddle | ||
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namespace ops = paddle::operators; | ||
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REGISTER_OP_NPU_KERNEL( | ||
matmul, ops::MatMulNPUKernel<paddle::platform::NPUDeviceContext, float>, | ||
ops::MatMulNPUKernel<paddle::platform::NPUDeviceContext, | ||
paddle::platform::float16>); | ||
REGISTER_OP_NPU_KERNEL( | ||
matmul_grad, | ||
ops::MatMulGradNPUKernel<paddle::platform::NPUDeviceContext, float>, | ||
ops::MatMulGradNPUKernel<paddle::platform::NPUDeviceContext, | ||
paddle::platform::float16>); |
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30 changes: 30 additions & 0 deletions
30
python/paddle/fluid/tests/unittests/npu/test_mixed_precision_npu.py
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
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import unittest | ||
import sys | ||
import paddle | ||
sys.path.append("..") | ||
import test_mixed_precision | ||
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paddle.enable_static() | ||
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class AMPTestNpu(test_mixed_precision.AMPTest): | ||
def setUp(self): | ||
self.place = paddle.NPUPlace(0) | ||
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if __name__ == '__main__': | ||
unittest.main() |
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