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115 lines
4.4 KiB
115 lines
4.4 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/channel.h"
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#include "paddle/fluid/framework/lod_rank_table.h"
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#include "paddle/fluid/framework/lod_tensor_array.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/reader.h"
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namespace pf = paddle::framework;
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static constexpr char kOutput[] = "Out";
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namespace paddle {
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namespace operators {
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class ChannelCreateOp : public framework::OperatorBase {
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public:
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ChannelCreateOp(const std::string &type,
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const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: framework::OperatorBase(type, inputs, outputs, attrs) {}
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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 &out = *scope.FindVar(Output(kOutput));
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// Determine the datatype and capacity of the channel to be created
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// from the attributes provided.
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auto dtype =
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static_cast<framework::proto::VarType::Type>(Attr<int>("data_type"));
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auto capacity = Attr<int>("capacity");
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// Based on the datatype, create a new channel holder initialized with
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// the given capacity. When capacity is 0, an unbuffered channel is
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// created.
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pf::ChannelHolder *ch = out.GetMutable<framework::ChannelHolder>();
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if (dtype == framework::proto::VarType::LOD_TENSOR) {
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ch->Reset<pf::LoDTensor>(capacity);
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} else if (dtype == framework::proto::VarType::SELECTED_ROWS) {
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ch->Reset<pf::SelectedRows>(capacity);
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} else if (dtype == framework::proto::VarType::LOD_RANK_TABLE) {
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ch->Reset<pf::LoDRankTable>(capacity);
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} else if (dtype == framework::proto::VarType::LOD_TENSOR_ARRAY) {
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ch->Reset<pf::LoDTensorArray>(capacity);
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} else if (dtype == framework::proto::VarType::READER) {
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ch->Reset<pf::ReaderHolder>(capacity);
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} else if (dtype == framework::proto::VarType::CHANNEL) {
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ch->Reset<pf::ChannelHolder>(capacity);
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} else if (dtype == framework::proto::VarType::BOOL) {
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ch->Reset<bool>(capacity);
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} else if (dtype == framework::proto::VarType::INT32) {
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ch->Reset<int>(capacity);
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} else if (dtype == framework::proto::VarType::INT64) {
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ch->Reset<int64_t>(capacity);
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} else if (dtype == framework::proto::VarType::FP32) {
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ch->Reset<float>(capacity);
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} else if (dtype == framework::proto::VarType::FP64) {
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ch->Reset<double>(capacity);
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} else {
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PADDLE_THROW(
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"Data type %d is not in "
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"[LOD_TENSOR, SELECTED_ROWS, LOD_RANK_TABLE, LOD_TENSOR_ARRAY, "
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"READER, CHANNEL, BOOL, INT32, INT64, FP32, FP64]",
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dtype);
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}
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}
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};
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class ChannelCreateOpOpInferShape : public framework::InferShapeBase {
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public:
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void operator()(framework::InferShapeContext *context) const override {
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PADDLE_ENFORCE(context->HasOutput(kOutput),
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"The output of ChannelCreate op must be set");
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context->SetOutputDim(kOutput, {1});
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}
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};
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class ChannelCreateOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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ChannelCreateOpMaker(OpProto *proto, OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddOutput(kOutput,
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"The object of a Channel type created by ChannelCreate Op.");
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AddAttr<int>("capacity", "The size of the buffer of Channel.")
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.SetDefault(0);
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AddAttr<int>("data_type", "The data type of elements inside the Channel.");
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AddComment(R"DOC(
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Channel Create Operator.
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This operator creates an object of the VarType Channel and returns it.
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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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REGISTER_OPERATOR(channel_create, paddle::operators::ChannelCreateOp,
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paddle::framework::EmptyGradOpMaker,
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paddle::operators::ChannelCreateOpMaker);
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