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114 lines
4.1 KiB
114 lines
4.1 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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#include "paddle/fluid/framework/data_type.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/math/math_function.h"
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namespace paddle {
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namespace operators {
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class FillConstantInferShape : public framework::InferShapeBase {
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public:
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void operator()(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of FillConstantOp should not be null.");
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auto &shape = ctx->Attrs().Get<std::vector<int64_t>>("shape");
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ctx->SetOutputDim("Out", framework::make_ddim(shape));
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}
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};
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class FillConstantOp : public framework::OperatorBase {
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public:
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using framework::OperatorBase::OperatorBase;
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private:
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void RunImpl(const framework::Scope &scope,
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const platform::Place &dev_place) const override {
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auto data_type =
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static_cast<framework::proto::VarType::Type>(Attr<int>("dtype"));
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auto value = Attr<float>("value");
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auto force_cpu = Attr<bool>("force_cpu");
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framework::Tensor *tensor = nullptr;
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auto &out_var = *scope.FindVar(Output("Out"));
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if (out_var.IsType<framework::LoDTensor>()) {
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tensor = out_var.GetMutable<framework::LoDTensor>();
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tensor->Resize(framework::make_ddim(Attr<std::vector<int64_t>>("shape")));
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} else if (out_var.IsType<framework::SelectedRows>()) {
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tensor = out_var.GetMutable<framework::SelectedRows>()->mutable_value();
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tensor->Resize(framework::make_ddim(Attr<std::vector<int64_t>>("shape")));
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} else {
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PADDLE_THROW(
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"fill constant op's output only"
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"supports SelectedRows and LoDTensor");
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}
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if (force_cpu) {
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auto cpu = platform::CPUPlace();
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tensor->mutable_data(cpu, framework::ToTypeIndex(data_type));
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} else {
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tensor->mutable_data(dev_place, framework::ToTypeIndex(data_type));
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}
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platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
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auto &dev_ctx = *pool.Get(dev_place);
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math::set_constant(dev_ctx, tensor, value);
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}
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};
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class FillConstantOpVarTypeInference : public framework::VarTypeInference {
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public:
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void operator()(const framework::OpDesc &op_desc,
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framework::BlockDesc *block) const override {}
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};
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class FillConstantOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddAttr<int>("dtype",
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"(int, default 5 (FP32)) "
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"Output data type")
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.SetDefault(framework::proto::VarType::FP32);
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AddAttr<std::vector<int64_t>>("shape",
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"(vector<int64_t>) The shape of the output");
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AddAttr<float>("value", "(float, default 0) The value to be filled")
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.SetDefault(0.0f);
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AddAttr<bool>("force_cpu",
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"(bool, default false) Force fill output variable to cpu "
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"memory. Otherwise, fill output variable to the running "
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"device")
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.SetDefault(false);
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AddOutput("Out",
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"(Tensor) Tensor of specified shape will be filled "
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"with the specified value");
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AddComment(R"DOC(
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FillConstantBatchSizeLike Operator.
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Fill up a variable with specified constant value.
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)DOC");
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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(fill_constant, ops::FillConstantOp,
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ops::FillConstantInferShape, ops::FillConstantOpMaker,
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paddle::framework::EmptyGradOpMaker,
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ops::FillConstantOpVarTypeInference);
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