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Paddle/paddle/fluid/operators/where_op.cc

159 lines
6.1 KiB

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