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138 lines
4.7 KiB
138 lines
4.7 KiB
/* Copyright (c) 2016 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/framework/operator.h"
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namespace paddle {
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namespace operators {
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class ElementwiseOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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using Tensor = framework::Tensor;
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void InferShape(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"),
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"Input(X) of elementwise op should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("Y"),
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"Input(Y) of elementwise op should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of elementwise op should not be null.");
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auto x_dim = ctx->GetInputDim("X");
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auto y_dim = ctx->GetInputDim("Y");
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PADDLE_ENFORCE_GE(x_dim.size(), y_dim.size(),
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"Rank of first input must >= rank of second input.");
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ctx->SetOutputDim("Out", x_dim);
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ctx->ShareLoD("X", /*->*/ "Out");
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}
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};
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class ElementwiseOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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ElementwiseOpMaker(OpProto* proto, OpAttrChecker* op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "(Tensor), The first input tensor of elementwise op.");
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AddInput("Y", "(Tensor), The second input tensor of elementwise op.");
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AddOutput("Out", "The output of elementwise op.");
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AddAttr<int>("axis",
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"(int, default -1). The start dimension index "
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"for broadcasting Y onto X.")
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.SetDefault(-1)
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.EqualGreaterThan(-1);
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comment_ = R"DOC(
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Limited Elementwise {name} Operator.
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The equation is:
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$${equation}$$
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$X$ is a tensor of any dimension and the dimensions of tensor $Y$ must be
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smaller than or equal to the dimensions of $X$.
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There are two cases for this operator:
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1. The shape of $Y$ is same with $X$;
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2. The shape of $Y$ is a subset of $X$.
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For case 2:
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$Y$ will be broadcasted to match the shape of $X$ and axis should be
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set to index of the start dimension to broadcast $Y$ onto $X$.
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For example
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.. code-block:: python
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shape(X) = (2, 3, 4, 5), shape(Y) = (,)
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shape(X) = (2, 3, 4, 5), shape(Y) = (5,)
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shape(X) = (2, 3, 4, 5), shape(Y) = (4, 5)
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shape(X) = (2, 3, 4, 5), shape(Y) = (3, 4), with axis=1
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shape(X) = (2, 3, 4, 5), shape(Y) = (2), with axis=0
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Either of the inputs $X$ and $Y$ or none can carry the LoD (Level of Details)
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information. However, the output only shares the LoD information with input $X$.
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)DOC";
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AddComment(comment_);
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}
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protected:
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std::string comment_;
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void Replace(std::string& src, std::string from, std::string to) {
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std::size_t len_from = std::strlen(from.c_str());
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std::size_t len_to = std::strlen(to.c_str());
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for (std::size_t pos = src.find(from); pos != std::string::npos;
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pos = src.find(from, pos + len_to)) {
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src.replace(pos, len_from, to);
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}
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}
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void SetComment(std::string name, std::string equation) {
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Replace(comment_, "{name}", name);
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Replace(comment_, "{equation}", equation);
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}
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};
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class ElementwiseOpGrad : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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using Tensor = framework::Tensor;
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void InferShape(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
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PADDLE_ENFORCE(ctx->HasInput("Y"), "Input(Y) should not be null");
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PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
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"Input(Out@GRAD) should not be null");
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auto x_dims = ctx->GetInputDim("X");
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auto y_dims = ctx->GetInputDim("Y");
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auto out_dims = ctx->GetInputDim(framework::GradVarName("Out"));
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PADDLE_ENFORCE_GE(x_dims.size(), y_dims.size(),
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"Rank of first input must >= rank of second input.");
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auto x_grad_name = framework::GradVarName("X");
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auto y_grad_name = framework::GradVarName("Y");
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if (ctx->HasOutput(x_grad_name)) {
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ctx->SetOutputDim(x_grad_name, x_dims);
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}
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if (ctx->HasOutput(y_grad_name)) {
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ctx->SetOutputDim(y_grad_name, y_dims);
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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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