chore: import upstream snapshot with attribution
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// Copyright (c) 2018 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/reader/ctr_reader.h"
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#include "paddle/fluid/operators/reader/reader_op_registry.h"
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#include "paddle/phi/core/operators/reader/dense_tensor_blocking_queue.h"
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namespace paddle {
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namespace operators {
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namespace reader {
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class CreateCTRReaderOp : 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 phi::Place& dev_place) const override {
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auto* out = scope.FindVar(Output("Out"))
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->template GetMutable<framework::ReaderHolder>();
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if (out->Get() != nullptr) return;
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const std::string& queue_name = Input("blocking_queue");
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auto* queue_holder_var = scope.FindVar(queue_name);
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PADDLE_ENFORCE_NOT_NULL(
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queue_holder_var,
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common::errors::PreconditionNotMet(
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"No DenseTensorBlockingQueueHolder variable with name %s found",
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queue_name));
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auto* queue_holder =
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queue_holder_var->template GetMutable<DenseTensorBlockingQueueHolder>();
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auto thread_num = Attr<int>("thread_num");
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auto sparse_slots = Attr<std::vector<std::string>>("sparse_slots");
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auto dense_slot_index = Attr<std::vector<int>>("dense_slot_index");
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auto sparse_slot_index = Attr<std::vector<int>>("sparse_slot_index");
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auto batch_size = Attr<int>("batch_size");
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auto file_type = Attr<std::string>("file_type");
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auto file_format = Attr<std::string>("file_format");
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auto file_list = Attr<std::vector<std::string>>("file_list");
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DataDesc data_desc(batch_size,
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file_list,
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file_type,
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file_format,
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dense_slot_index,
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sparse_slot_index,
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sparse_slots);
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VLOG(1) << data_desc;
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out->Reset(std::make_shared<CTRReader>(
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queue_holder->GetQueue(), thread_num, data_desc));
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}
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};
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class CreateCTRReaderOpMaker : public FileReaderMakerBase {
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protected:
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void Apply() override {
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AddInput("blocking_queue",
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"Name of the `DenseTensorBlockingQueueHolder` variable");
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AddAttr<int>("thread_num", "the thread num to read data");
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AddAttr<int>("batch_size", "the batch size of read data");
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AddAttr<std::string>("file_type", "plain or gzip").SetDefault("plain");
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AddAttr<std::string>("file_format", "svm or csv").SetDefault("csv");
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AddAttr<std::vector<std::string>>("file_list",
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"The list of files that need to read");
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AddAttr<std::vector<int>>(
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"dense_slot_index",
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"the dense slots id that should be extract from file")
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.SetDefault({});
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AddAttr<std::vector<int>>(
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"sparse_slot_index",
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"the sparse slots id that should be extract from file")
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.SetDefault({});
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AddAttr<std::vector<std::string>>("sparse_slots",
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"the sparse slots id that should be "
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"extract from file, used when file "
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"format is svm");
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AddComment(R"DOC(
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Create CTRReader to support read ctr data with cpp.
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)DOC");
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}
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};
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} // namespace reader
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} // namespace operators
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} // namespace paddle
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namespace reader = ::paddle::operators::reader;
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REGISTER_FILE_READER_OPERATOR(create_ctr_reader,
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reader::CreateCTRReaderOp,
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reader::CreateCTRReaderOpMaker);
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