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105 lines
4.0 KiB
105 lines
4.0 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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#pragma once
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#include <algorithm>
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#include <vector>
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#include "paddle/fluid/framework/lod_tensor.h"
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#include "paddle/fluid/platform/device_context.h"
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namespace paddle {
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namespace operators {
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namespace math {
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enum PadLayout { kBatchLengthWidth = 0, kLengthBatchWidth };
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enum CopyType { kSeqToPad, kPadToSeq };
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inline static size_t MaximumSequenceLength(
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const framework::Vector<size_t>& seq_offset) {
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size_t seq_num = seq_offset.size() - 1;
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size_t max_seq_len = 0;
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for (size_t i = 0; i < seq_num; ++i) {
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max_seq_len = std::max(max_seq_len, seq_offset[i + 1] - seq_offset[i]);
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}
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return max_seq_len;
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}
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inline static void CheckDims(const framework::DDim& seq_tensor_dims,
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const framework::DDim& pad_tensor_dims,
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const framework::Vector<size_t>& seq_offset,
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int64_t padded_seq_len, int64_t step_width,
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const PadLayout& layout) {
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PADDLE_ENFORCE_EQ(static_cast<size_t>(seq_tensor_dims[0]), seq_offset.back(),
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"Value of 1st dimension of the sequence tensor should be "
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"equal to sum of lengths of all sequences.");
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PADDLE_ENFORCE(seq_tensor_dims.size() + 1 == pad_tensor_dims.size() ||
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seq_tensor_dims.size() == pad_tensor_dims.size(),
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"pad_tensor's rank should be 1 greater than seq_tensor's "
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"rank, or be equal with it.");
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}
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/*
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* \brief Padding/Unpadding LoDTensor to/from normal Tensor of the shape
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* [max_sequence_length, num_sequences, sequence_width].
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*
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* Padding sequence:
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* padding[i] = seq[lod[level][i]]
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* Unpadding sequence:
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* seq[lod[level][i]] = padding[i]
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*
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* All sequences will be padded to the same length and stored in a transposed
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* shape.
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* Example:
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* seq (s0, s0, s0, s0; s1, s1; s2, s2, s2; s3)
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* padding (s0, s1, s2, s3; s0, s1, s2, 0; s0, 0, s2, 0; s0, 0, 0, 0)
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*
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* \param context device context of this functor.
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* \param seq LoDTensor which is stored in sequence format, the shape
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* is [total_sequence_length, sequence_width] where
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* total_sequence_length is the sum of all sequences'
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* length.
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* \param padding Tensor which is padded to the same length, the shape is
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* [max_sequence_length, num_sequences, sequence_width].
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* \param norm_by_times whether dividing sequence's length.
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*
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* \note transposition is also done in this functor.
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*/
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template <typename DeviceContext, typename T>
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class PaddingLoDTensorFunctor {
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public:
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void operator()(const DeviceContext& context,
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const framework::LoDTensor& seq_tensor,
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framework::LoDTensor* pad_tensor,
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const framework::LoDTensor& pad_value, int pad_seq_len = -1,
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int lod_level = 0, bool norm_by_times = false,
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const PadLayout layout = kBatchLengthWidth);
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};
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template <typename DeviceContext, typename T>
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class UnpaddingLoDTensorFunctor {
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public:
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void operator()(const DeviceContext& context,
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const framework::LoDTensor& pad_tensor,
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framework::LoDTensor* seq_tensor, int pad_seq_len = -1,
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int lod_level = 0, bool norm_by_times = false,
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const PadLayout layout = kBatchLengthWidth);
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};
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} // namespace math
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} // namespace operators
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} // namespace paddle
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