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111 lines
3.1 KiB
111 lines
3.1 KiB
7 years ago
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/* 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 <vector>
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#include "paddle/framework/lod_tensor.h"
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namespace paddle {
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namespace framework {
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/*
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* DyBatchSeqPosition stores indices of the basic element in tensor. It is used
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* after lod-tensor's re-assembling, its info can be used to recover the order
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* in original lod-tensor.
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*/
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struct DySeqMeta {
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size_t begin;
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size_t end; // not included
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size_t ori_idx;
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};
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/*
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* TensorArray is a C-array-like array of tensors, it is meant to be used with
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* dynamic iteration primitives such as while_loop. It is used to segment inputs
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* and store states in all time steps.
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*
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* By providing some methods similar to a C++ array, the difinition of some
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* state-based dynamic models such as RNN cound be more natural and highly
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* flexible.
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*/
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class TensorArray {
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public:
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using value_type = float;
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// max number of values allowed to store.
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const size_t MAX_SIZE{100000};
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/*
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* Read the value at location `index` in the `TensorArray`.
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*/
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const LoDTensor &Read(size_t index) const;
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/*
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* Write value into the index of the TensorArray.
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*/
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void Write(size_t index, const LoDTensor &value);
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/*
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* Write value into the index of the TensorArray, with memory shared.
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*/
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void WriteShared(size_t index, const LoDTensor &value);
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/*
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* Recover the original LoD-arranged LoDTensor with the `values`, `level` and
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* `indice_map`.
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*/
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LoDTensor Pack(size_t level, const std::vector<DySeqMeta> &meta,
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const LoD &lod) const;
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/*
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* Split LoDTensor in some `level` and write the generated batches to
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* `values`, if set `desend`, will sort by length in descending order else in
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* ascending order.
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*/
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std::vector<DySeqMeta> Unpack(const LoDTensor &source, int level,
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bool length_desend);
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/*
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* Pack the values into a tensor with rank one higher than each tensor in
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* values.
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*/
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LoDTensor Stack() const;
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/*
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* Unpacks the given division of a rank-`R` tensor into rank-`(R-1)` tensors.
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*/
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void Unstack(const LoDTensor &source) const;
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/*
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* Unpacks the given division of a rank-`R` tensor into rank-`(R-1)` tensors,
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* with memory of tensors shared.
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*/
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void UnstackShared(const LoDTensor &source) const;
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/*
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* Return the number of values.
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*/
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size_t size() const;
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protected:
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void Unstack(const LoDTensor &source, bool data_shared) const;
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private:
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mutable std::vector<LoDTensor> values_;
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}; // class TensorArray
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} // namespace framework
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} // namespace paddle
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