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125 lines
4.4 KiB
125 lines
4.4 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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#pragma once
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#include <paddle/utils/PythonUtil.h>
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#include "DataFormat.pb.h"
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#include "DataProvider.h"
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#include <vector>
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namespace paddle {
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class PyDataProvider : public DataProvider {
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public:
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PyDataProvider(const DataConfig& config,
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bool useGpu,
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bool loadDataAll = true);
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virtual void reset();
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// Note this size includes the sequences which are skipped because they
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// are longer than the batch size
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virtual int64_t getSize() {
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LOG(FATAL) << "Not implement yet";
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return -1;
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}
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virtual void shuffle();
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virtual int64_t getNextBatchInternal(int64_t size, DataBatch* batch);
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protected:
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struct ProtoSlot;
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// return false if each each sample is one sequence, i.e., independent
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// of other samples.
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inline bool iidData() const { return isIID_; }
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void parseHeaderData(const std::string& headerData);
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void fillDenseSlot(ProtoSlot& slot, char*& data, const char* dataEnd);
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void fillSparseNonValueSlot(ProtoSlot& slot,
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char*& data,
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const char* dataEnd);
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void fillSparseValueSlot(ProtoSlot& slot, char*& data, const char* dataEnd);
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void fillIndexSlot(ProtoSlot& slot, char*& data, const char* dataEnd);
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void fillStringSlot(ProtoSlot& slot, char*& data, const char* dataEnd);
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void fillSlotsByStr(const std::string& samples);
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void handleDenseSlot(ProtoSlot& slot,
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size_t slotIndex,
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std::vector<Argument>& cpuArguments);
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void handleSparseNonValueSlot(ProtoSlot& slot,
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size_t slotIndex,
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std::vector<Argument>& cpuArguments);
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void handleSparseValueSlot(ProtoSlot& slot,
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size_t slotIndex,
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std::vector<Argument>& cpuArguments);
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void handleIndexSlot(ProtoSlot& slot,
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size_t slotIndex,
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std::vector<Argument>& cpuArguments);
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void handleStringSlot(ProtoSlot& slot,
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size_t slotIndex,
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std::vector<Argument>& cpuArguments);
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void resetSlots();
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void loadData(const std::vector<std::string>& fileList);
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protected:
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struct ProtoSlot {
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SlotDef::SlotType type;
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int dim;
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unsigned int sampleNum;
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unsigned int sequenceNum;
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unsigned int subSequenceNum;
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// Store the data of index type slot
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std::vector<int> indexData;
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// Store the data of dense type slot
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std::vector<real> denseData;
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// Store the data of sparseNonValue type slot
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std::vector<sparse_non_value_t> sparseNonValueData;
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// Store the data of sparseValue type slot
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std::vector<sparse_float_value_t> sparseFloatValueData;
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// Used to store the index of each sample in slot values
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std::vector<int64_t> indices;
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// The starting position of each sequence in samples
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// The last element should be the number of samples
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// If empty, each sample is one sequence.
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std::vector<size_t> sequenceStartPositions;
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// The index id of sequences in slot
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std::vector<int64_t> sampleSequenceIdVec;
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// The starting position of each subsequence in samples
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// The last element should be the number of subsequence
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// If empty, each sequence of sample has no subsequence.
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std::vector<size_t> subSequenceStartPositions;
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// Store the data of string type slot
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std::vector<std::string> strData;
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};
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std::vector<ProtoSlot> slots_;
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PyObjectPtr classInstance_;
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unsigned int batchSize_;
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unsigned int slotNum_;
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// if use sequence, isIID_ equals false, otherwise it is true.
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bool isIID_;
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// The name of python module name
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std::string pyModuleName_;
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// The name of python class name
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std::string pyClassName_;
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// User args set in config
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std::map<std::string, std::string> pyUserArgs_;
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ThreadLocalD<DataBatch> cpuBatch_;
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ThreadLocalD<DataBatch> gpuBatch_;
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};
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} // namespace paddle
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