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137 lines
4.5 KiB
137 lines
4.5 KiB
/* Copyright (c) 2019 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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#pragma once
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/math/blas.h"
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#include "paddle/fluid/operators/math/math_function.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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template <typename DeviceContext, typename T>
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class FSPOpKernel : 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* x = context.Input<Tensor>("X");
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auto* y = context.Input<Tensor>("Y");
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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 x_dims = x->dims();
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auto y_dims = y->dims();
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auto batch_size = x_dims[0];
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auto x_channel = x_dims[1];
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auto y_channel = y_dims[1];
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auto height = x_dims[2];
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auto width = x_dims[3];
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auto blas = math::GetBlas<DeviceContext, T>(context);
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math::MatDescriptor x_mat_desc;
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x_mat_desc.height_ = x_channel;
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x_mat_desc.width_ = height * width;
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x_mat_desc.batch_size_ = batch_size;
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x_mat_desc.stride_ = x_channel * height * width;
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math::MatDescriptor y_mat_desc;
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y_mat_desc.height_ = height * width;
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y_mat_desc.width_ = y_channel;
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y_mat_desc.batch_size_ = batch_size;
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y_mat_desc.stride_ = y_channel * height * width;
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y_mat_desc.trans_ = true;
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blas.MatMul(*x, x_mat_desc, *y, y_mat_desc,
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static_cast<T>(1.0 / (height * width)), output,
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static_cast<T>(0.0));
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}
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};
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template <typename DeviceContext, typename T>
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class FSPGradOpKernel : 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* d_x = context.Output<Tensor>(framework::GradVarName("X"));
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auto* d_y = context.Output<Tensor>(framework::GradVarName("Y"));
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if (d_x == nullptr && d_y == nullptr) {
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return;
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}
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auto* d_out = context.Input<Tensor>(framework::GradVarName("Out"));
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auto d_out_dims = d_out->dims();
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auto batch_size = d_out_dims[0];
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auto x_channel = d_out_dims[1];
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auto y_channel = d_out_dims[2];
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int64_t h = 0;
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int64_t w = 0;
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auto blas = math::GetBlas<DeviceContext, T>(context);
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math::SetConstant<DeviceContext, T> set_zero;
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if (d_x != nullptr) {
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d_x->mutable_data<T>(context.GetPlace());
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set_zero(context.template device_context<DeviceContext>(), d_x,
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static_cast<T>(0));
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auto* y = context.Input<Tensor>("Y");
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auto y_dims = y->dims();
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h = y_dims[2];
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w = y_dims[3];
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math::MatDescriptor d_out_mat_desc;
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d_out_mat_desc.height_ = x_channel;
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d_out_mat_desc.width_ = y_channel;
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d_out_mat_desc.batch_size_ = batch_size;
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d_out_mat_desc.stride_ = x_channel * y_channel;
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math::MatDescriptor y_mat_desc;
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y_mat_desc.height_ = y_channel;
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y_mat_desc.width_ = h * w;
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y_mat_desc.batch_size_ = batch_size;
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y_mat_desc.stride_ = y_channel * h * w;
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blas.MatMul(*d_out, d_out_mat_desc, *y, y_mat_desc,
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static_cast<T>(1.0 / (h * w)), d_x, static_cast<T>(0.0));
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}
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if (d_y != nullptr) {
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d_y->mutable_data<T>(context.GetPlace());
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set_zero(context.template device_context<DeviceContext>(), d_y,
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static_cast<T>(0));
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auto* x = context.Input<Tensor>("X");
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auto x_dims = x->dims();
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h = x_dims[2];
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w = x_dims[3];
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math::MatDescriptor d_out_mat_desc;
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d_out_mat_desc.height_ = y_channel;
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d_out_mat_desc.width_ = x_channel;
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d_out_mat_desc.batch_size_ = batch_size;
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d_out_mat_desc.stride_ = x_channel * y_channel;
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d_out_mat_desc.trans_ = true;
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math::MatDescriptor x_mat_desc;
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x_mat_desc.height_ = x_channel;
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x_mat_desc.width_ = h * w;
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x_mat_desc.batch_size_ = batch_size;
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x_mat_desc.stride_ = x_channel * h * w;
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blas.MatMul(*d_out, d_out_mat_desc, *x, x_mat_desc,
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static_cast<T>(1.0 / (h * w)), d_y, static_cast<T>(0.0));
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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