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129 lines
4.5 KiB
129 lines
4.5 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/log_softmax_op.h"
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#include <string>
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#include <unordered_map>
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#include "paddle/fluid/operators/common_infer_shape_functions.h"
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namespace paddle {
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namespace operators {
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class LogSoftmaxOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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return UnaryOpUnchangedInferShapeCheckAxis(ctx);
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext& ctx) const override {
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return framework::OpKernelType(
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OperatorWithKernel::IndicateVarDataType(ctx, "X"),
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ctx.device_context());
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}
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};
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class LogSoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X",
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"The input tensor of softmax, "
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"whose dimension :attr:`axis` is the input_feature_dimensions.");
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AddOutput("Out", "The normalized values with the same shape as X.");
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AddAttr<int>("axis",
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"The dimension index of Input(x) to perform log_softmax,"
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"default -1 for last dimension")
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.SetDefault(-1);
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AddComment(R"DOC(
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LogSoftmax Operator.
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)DOC");
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}
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};
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class LogSoftmaxOpInferVarType
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: public framework::PassInDtypeAndVarTypeToOutput {
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protected:
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std::unordered_map<std::string, std::string>& GetInputOutputWithSameType()
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const override {
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static std::unordered_map<std::string, std::string> m{{"X", /*->*/ "Out"}};
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return m;
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}
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};
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class LogSoftmaxGradOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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OP_INOUT_CHECK(ctx->HasInput("Out"), "Input", "Out", "log_softmax_grad");
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OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
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"Out@grad", "log_softmax_grad");
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PADDLE_ENFORCE_EQ(
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ctx->GetInputDim("Out"),
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ctx->GetInputDim(framework::GradVarName("Out")),
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platform::errors::InvalidArgument("Input(Out) and its gradients "
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"should have the same shape."));
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ctx->SetOutputDim(framework::GradVarName("X"),
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ctx->GetInputDim(framework::GradVarName("Out")));
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext& ctx) const override {
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return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType(
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ctx, framework::GradVarName("Out")),
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ctx.device_context());
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}
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};
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template <typename T>
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class LogSoftmaxGradOpMaker : public framework::SingleGradOpMaker<T> {
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public:
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using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
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protected:
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void Apply(GradOpPtr<T> op) const override {
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op->SetType("log_softmax_grad");
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op->SetInput("Out", this->Output("Out"));
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op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
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op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
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op->SetAttrMap(this->Attrs());
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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_OPERATOR(log_softmax, ops::LogSoftmaxOp, ops::LogSoftmaxOpMaker,
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ops::LogSoftmaxOpInferVarType,
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ops::LogSoftmaxGradOpMaker<paddle::framework::OpDesc>,
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ops::LogSoftmaxGradOpMaker<paddle::imperative::OpBase>);
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REGISTER_OPERATOR(log_softmax_grad, ops::LogSoftmaxGradOp);
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REGISTER_OP_CPU_KERNEL(
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log_softmax,
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ops::LogSoftmaxKernel<paddle::platform::CPUDeviceContext, float>,
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ops::LogSoftmaxKernel<paddle::platform::CPUDeviceContext, double>);
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REGISTER_OP_CPU_KERNEL(
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log_softmax_grad,
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ops::LogSoftmaxGradKernel<paddle::platform::CPUDeviceContext, float>,
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ops::LogSoftmaxGradKernel<paddle::platform::CPUDeviceContext, double>);
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