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159 lines
6.1 KiB
159 lines
6.1 KiB
// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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/where_op.h"
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namespace paddle {
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namespace operators {
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class WhereOp : 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("Condition"), "Input", "Condition", "Where");
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OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Where");
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OP_INOUT_CHECK(ctx->HasInput("Y"), "Input", "Y", "Where");
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OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Where");
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auto cond_dims = ctx->GetInputDim("Condition");
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auto x_dims = ctx->GetInputDim("X");
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auto y_dims = ctx->GetInputDim("Y");
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PADDLE_ENFORCE_EQ(
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cond_dims, x_dims,
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platform::errors::InvalidArgument(
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"The dims of Inputs(Condition) and Inputs(X) should be same. "
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"But received Condition's shape is [%s], X's shape is [%s]",
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cond_dims, x_dims));
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PADDLE_ENFORCE_EQ(x_dims, y_dims,
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platform::errors::InvalidArgument(
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"The dims of Inputs(X) and Inputs(Y) should be same. "
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"But received X's shape is [%s], Y's shape is [%s]",
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x_dims, y_dims));
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ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
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ctx->ShareLoD("X", /*->*/ "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(
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OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
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}
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};
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class WhereGradOp : 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("Condition"), "Input", "Condition", "Where");
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OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Where");
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OP_INOUT_CHECK(ctx->HasInput("Y"), "Input", "Y", "Where");
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OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
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framework::GradVarName("Out"), "Where");
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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 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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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.GetPlace());
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}
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};
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class WhereOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("Condition",
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"(Tensor) A bool tensor whose rank is at least 1. When Condition "
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"is True, yield x, otherwise yield y");
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AddInput("X",
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"(Tensor), The first input tensor of where op. When the "
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"corresponding position of the condition is true, the output "
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"takes the element of X.");
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AddInput("Y",
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"(Tensor), The second input tensor of where op. When the "
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"corresponding position of condition is false, the output takes "
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"the element of Y.");
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AddOutput("Out", "(Tensor), The output tensor of where op.");
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AddComment(R"DOC(
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Where Operator.
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Return a tensor of elements selected from either $X$ or $Y$, depending on condition.
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The equation is:
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$$
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Out_i =
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\begin{cases}
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\X_i, \quad \text{if} \ cond_i is True \\
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\Y_i, \quad \text{if} \ cond_i is False \\
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\end{cases}
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$$
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)DOC");
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}
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};
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template <typename T>
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class WhereOpGradMaker : 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> grad) const override {
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grad->SetType("where_grad");
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grad->SetInput("Condition", this->Input("Condition"));
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grad->SetInput("X", this->Input("X"));
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grad->SetInput("Y", this->Input("Y"));
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grad->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
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grad->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
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grad->SetOutput(framework::GradVarName("Y"), this->InputGrad("Y"));
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}
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};
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DECLARE_NO_NEED_BUFFER_VARS_INFERER(WhereGradNoNeedBufferVarsInferer, "X", "Y");
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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(where, ops::WhereOp, ops::WhereOpMaker,
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ops::WhereOpGradMaker<paddle::framework::OpDesc>,
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ops::WhereOpGradMaker<paddle::imperative::OpBase>);
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REGISTER_OPERATOR(where_grad, ops::WhereGradOp,
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ops::WhereGradNoNeedBufferVarsInferer);
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REGISTER_OP_CPU_KERNEL(
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where, ops::WhereKernel<paddle::platform::CPUDeviceContext, float>,
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ops::WhereKernel<paddle::platform::CPUDeviceContext, double>,
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ops::WhereKernel<paddle::platform::CPUDeviceContext, int>,
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ops::WhereKernel<paddle::platform::CPUDeviceContext, int64_t>);
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REGISTER_OP_CPU_KERNEL(
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where_grad, ops::WhereGradKernel<paddle::platform::CPUDeviceContext, float>,
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ops::WhereGradKernel<paddle::platform::CPUDeviceContext, double>,
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ops::WhereGradKernel<paddle::platform::CPUDeviceContext, int>,
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ops::WhereGradKernel<paddle::platform::CPUDeviceContext, int64_t>);
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