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73 lines
2.7 KiB
73 lines
2.7 KiB
/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/fluid/operators/mean_op.h"
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#ifdef PADDLE_WITH_XPU
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#include <memory>
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#include <string>
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#include <unordered_map>
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T>
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class MeanXPUKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* input = context.Input<Tensor>("X");
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auto* output = context.Output<Tensor>("Out");
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output->mutable_data<T>(context.GetPlace());
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auto& dev_ctx = context.template device_context<DeviceContext>();
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const float* x_data = input->data<float>();
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float* y_data = output->data<float>();
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int r = xpu::mean(dev_ctx.x_context(), x_data, y_data, input->numel());
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PADDLE_ENFORCE_EQ(
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r, xpu::Error_t::SUCCESS,
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platform::errors::External(
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"XPU kernel error, Mean op execution not succeed, error code=%d",
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r));
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}
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};
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template <typename DeviceContext, typename T>
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class MeanGradXPUKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto OG = context.Input<Tensor>(framework::GradVarName("Out"));
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PADDLE_ENFORCE_EQ(OG->numel(), 1, platform::errors::InvalidArgument(
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"Mean Gradient should be scalar"));
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auto IG = context.Output<Tensor>(framework::GradVarName("X"));
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IG->mutable_data<T>(context.GetPlace());
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auto& dev_ctx = context.template device_context<DeviceContext>();
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float* dx = IG->data<float>();
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const float* dy = OG->data<float>();
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int r = xpu::mean_grad(dev_ctx.x_context(), dx, dy, IG->numel());
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PADDLE_ENFORCE_EQ(
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r, xpu::Error_t::SUCCESS,
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platform::errors::External(
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"XPU kernel error. Mean_grad execution not succeed, error code=%d",
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r));
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_XPU_KERNEL(
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mean, ops::MeanXPUKernel<paddle::platform::XPUDeviceContext, float>);
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REGISTER_OP_XPU_KERNEL(
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mean_grad,
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ops::MeanGradXPUKernel<paddle::platform::XPUDeviceContext, float>);
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#endif
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