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Paddle/paddle/operators/mul_op.h

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3.7 KiB

/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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.
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,
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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. */
#pragma once
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#include "paddle/operators/math/math_function.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/op_registry.h"
namespace paddle {
namespace operators {
using Tensor = framework::Tensor;
template <typename T, int MajorType = Eigen::RowMajor,
typename IndexType = Eigen::DenseIndex>
using EigenMatrix = framework::EigenMatrix<T, MajorType, IndexType>;
template <typename Place, typename T>
class MulKernel : public framework::OpKernel {
public:
void Compute(const framework::ExecutionContext& context) const override {
const Tensor* x = context.Input<Tensor>("X");
const Tensor* y = context.Input<Tensor>("Y");
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Tensor* z = context.Output<Tensor>("Out");
const Tensor x_matrix =
x->dims().size() > 2
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? framework::ReshapeToMatrix<T>(
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*x, context.template Attr<int>("x_num_col_dims"))
: *x;
const Tensor y_matrix =
y->dims().size() > 2
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? framework::ReshapeToMatrix<T>(
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*y, context.template Attr<int>("y_num_col_dims"))
: *y;
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z->mutable_data<T>(context.GetPlace());
math::matmul<Place, T>(context.device_context(), x_matrix, false, y_matrix,
false, 1, z, 0);
}
};
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template <typename Place, typename T>
class MulGradKernel : public framework::OpKernel {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
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int x_num_col_dims = ctx.template Attr<int>("x_num_col_dims");
int y_num_col_dims = ctx.template Attr<int>("y_num_col_dims");
const Tensor* x = ctx.Input<Tensor>("X");
const Tensor* y = ctx.Input<Tensor>("Y");
const Tensor x_matrix =
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x->dims().size() > 2 ? framework::ReshapeToMatrix<T>(*x, x_num_col_dims)
: *x;
const Tensor y_matrix =
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y->dims().size() > 2 ? framework::ReshapeToMatrix<T>(*y, y_num_col_dims)
: *y;
const Tensor* dout = ctx.Input<Tensor>(framework::GradVarName("Out"));
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Tensor* dx = ctx.Output<Tensor>(framework::GradVarName("X"));
Tensor* dy = ctx.Output<Tensor>(framework::GradVarName("Y"));
if (dx) {
dx->mutable_data<T>(ctx.GetPlace());
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Tensor dx_matrix = dx->dims().size() > 2 ? framework::ReshapeToMatrix<T>(
*dx, x_num_col_dims)
: *dx;
// dx = dout * y'. dx: M x K, dout : M x N, y : K x N
math::matmul<Place, T>(ctx.device_context(), *dout, false, y_matrix, true,
1, &dx_matrix, 0);
}
if (dy) {
dy->mutable_data<T>(ctx.GetPlace());
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Tensor dy_matrix = dy->dims().size() > 2 ? framework::ReshapeToMatrix<T>(
*dy, y_num_col_dims)
: *dy;
// dy = x' * dout. dy K x N, dout : M x N, x : M x K
math::matmul<Place, T>(ctx.device_context(), x_matrix, true, *dout, false,
1, &dy_matrix, 0);
}
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}
};
} // namespace operators
} // namespace paddle