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Paddle/paddle/fluid/operators/isfinite_op.cc

115 lines
4.4 KiB

// Copyright (c) 2018 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/isfinite_op.h"
#include <string>
#include <vector>
namespace paddle {
namespace operators {
class OverflowOp : public framework::OperatorWithKernel {
public:
OverflowOp(const std::string &type, const framework::VariableNameMap &inputs,
const framework::VariableNameMap &outputs,
const framework::AttributeMap &attrs)
: OperatorWithKernel(type, inputs, outputs, attrs) {}
void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE(ctx->HasInputs("X"), "Inputs(X) should not be null");
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"Output(Out) of OverflowOp should not be null.");
ctx->SetOutputDim("Out", {1});
}
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext &ctx) const override {
int dtype = -1;
auto *x_var = ctx.InputVar("X");
if (x_var->IsType<framework::LoDTensor>()) {
dtype = x_var->Get<framework::LoDTensor>().type();
} else if (x_var->IsType<framework::SelectedRows>()) {
dtype = x_var->Get<framework::SelectedRows>().value().type();
} else {
PADDLE_THROW("Cannot find the input data type by all input data");
}
return framework::OpKernelType(framework::proto::VarType::Type(dtype),
ctx.GetPlace());
}
};
class OverflowOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
AddInput("X", "(Tensor) The input tensors of overflow operator.");
AddOutput("Out",
"(Tensor) 1-dim tensor, contains a bool scalar. The output "
"tensor of overflow operator.");
AddComment(string::Sprintf(R"DOC(
Overflow %s operator.
$$Out = any(X)$$
If any X contains Inf or Nan, the Out will generate a indicator.
Out = Inf if any X contains Inf,
Out = Nan if any X contains Nan,
Out = 0 if no Inf/Nan detected.
If X contains both Inf/Nan, it will return the first indicator it meeted.
%s
)DOC",
GetName(), GetComments()));
}
protected:
virtual std::string GetName() const = 0;
virtual std::string GetComments() const = 0;
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
#define REGISTER_OP_MAKER(op_type, comment) \
namespace paddle { \
namespace operators { \
class _##op_type##OverflowOpMaker \
: public ::paddle::operators::OverflowOpMaker { \
protected: \
std::string GetName() const { return #op_type; } \
std::string GetComments() const { return comment; } \
}; \
} \
} \
REGISTER_OPERATOR(op_type, ops::OverflowOp, \
ops::_##op_type##OverflowOpMaker, \
paddle::framework::EmptyGradOpMaker)
#define REGISTER_OVERFLOW_CPU_KERNEL(op_type, functor) \
REGISTER_OP_CPU_KERNEL( \
op_type, ops::OverflowKernel<paddle::platform::CPUDeviceContext, int, \
ops::functor>, \
ops::OverflowKernel<paddle::platform::CPUDeviceContext, float, \
ops::functor>, \
ops::OverflowKernel<paddle::platform::CPUDeviceContext, double, \
ops::functor>);
REGISTER_OP_MAKER(isinf, "isinf(X)");
REGISTER_OP_MAKER(isnan, "isnan(X)");
REGISTER_OP_MAKER(isfinite, "isfinite(X)");
FOR_EACH_KERNEL_FUNCTOR(REGISTER_OVERFLOW_CPU_KERNEL);