add string implementation, can handle partial string slices finish core implementation, added Index object fix up the logic add in new SliceOption object, cleaning up testspull/5300/head
nhussain
5 years ago
parent
d0e49c5cf8
commit
77d507279c
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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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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*/
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#include <string>
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#include <vector>
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#include <iostream>
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#include "minddata/dataset/core/tensor_helpers.h"
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namespace mindspore {
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namespace dataset {
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void IndexGeneratorHelper(int8_t depth, std::vector<dsize_t> *numbers,
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const std::vector<mindspore::dataset::SliceOption> &slice_list,
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std::vector<std::vector<dsize_t>> *matrix) {
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// for loop changes if its an index instead of a slice object
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if (depth > 0) {
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dsize_t new_depth = depth - 1;
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dsize_t curr_ind = numbers->size() - depth;
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if (slice_list[curr_ind].slice_.valid()) {
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dsize_t increment = slice_list[curr_ind].slice_.step_;
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if (increment > 0) {
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for (int i = slice_list[curr_ind].slice_.start_; i < slice_list[curr_ind].slice_.stop_;
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i = i + slice_list[curr_ind].slice_.step_) {
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(*numbers)[curr_ind] = i;
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IndexGeneratorHelper(new_depth, numbers, slice_list, matrix);
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}
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} else {
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for (int i = slice_list[curr_ind].slice_.start_; i > slice_list[curr_ind].slice_.stop_;
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i = i + slice_list[curr_ind].slice_.step_) {
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(*numbers)[curr_ind] = i;
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IndexGeneratorHelper(new_depth, numbers, slice_list, matrix);
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}
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}
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} else {
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for (int i = 0; i < slice_list[curr_ind].indices_.size(); i++) {
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(*numbers)[curr_ind] = slice_list[curr_ind].indices_[i];
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IndexGeneratorHelper(new_depth, numbers, slice_list, matrix);
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}
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}
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} else {
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(*matrix).emplace_back((*numbers));
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}
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}
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// Used to generate slice indices
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std::vector<std::vector<dsize_t>> IndexGenerator(const std::vector<mindspore::dataset::SliceOption> &slice_list) {
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int8_t depth = slice_list.size();
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std::vector<dsize_t> numbers(depth, 0);
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std::vector<std::vector<dsize_t>> matrix(0, std::vector<dsize_t>(depth, 0));
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IndexGeneratorHelper(depth, &numbers, slice_list, &matrix);
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return matrix;
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}
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} // namespace dataset
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} // namespace mindspore
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@ -0,0 +1,81 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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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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*/
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#ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_CORE_TENSOR_HELPERS_H_
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#define MINDSPORE_CCSRC_MINDDATA_DATASET_CORE_TENSOR_HELPERS_H_
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#include <memory>
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#include <vector>
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#include "minddata/dataset/core/constants.h"
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namespace mindspore {
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namespace dataset {
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class Slice {
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public:
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Slice() : start_(0), stop_(0), step_(0) {}
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Slice(dsize_t start, dsize_t stop, dsize_t step) : start_(start), stop_(stop), step_(step) {}
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Slice(dsize_t start, dsize_t stop) : start_(start), stop_(stop), step_(1) {}
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explicit Slice(dsize_t stop) : start_(0), stop_(stop), step_(1) {}
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Slice(Slice const &slice) = default;
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~Slice() = default;
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bool valid() const { return !(start_ == 0 && stop_ == 0 && step_ == 0); }
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dsize_t start_;
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dsize_t stop_;
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dsize_t step_;
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};
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class SliceOption {
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public:
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explicit SliceOption(bool all) : all_(all) {}
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explicit SliceOption(std::vector<dsize_t> indices) : indices_(indices) {}
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explicit SliceOption(Slice slice) : slice_(slice) {}
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SliceOption(SliceOption const &slice) = default;
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// only one of the following will be valid
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// given indices to slice the Tensor.
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std::vector<dsize_t> indices_ = {};
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// Slice object. All start, stop and step are 0 if invalid.
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Slice slice_;
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bool all_ = false;
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};
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/// Recursive helper function to generate indices based on vector of SliceOptions. It recursively iterates through each
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/// range represented by slice_options to generate a list of indices to be sliced.
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/// \param[out] matrix Generated nested vector of indices
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/// Example: For a 4 x 2 tensor, and with slice_list = {SliceOption({0})} (the first row), matrix will become
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/// {{0}}. For slice_list = {SliceOption(all), SliceOption({0})} (the first column), matrix will become
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/// {{0, 0}, {1, 0}, {2, 0}, {3, 0}}.
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/// For slice_list = {SliceOption({0, 2})}, matrix will become {{0}, {2}}. The size of each nested array is always
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/// equal to (slice_list).size().
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/// \param[in] depth used to keep track of recursion level
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/// \param[in] numbers vector used to represent current index
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/// \param[in] matrix 2D vector to be populated with desired indices
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/// \param[in] slice_options vector of SliceOption objects
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void IndexGeneratorHelper(int8_t depth, std::vector<dsize_t> *numbers, const std::vector<SliceOption> &slice_list,
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std::vector<std::vector<dsize_t>> *matrix);
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/// Generate indices based on vector of SliceOptions
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/// Calls the recursive helper function IndexGeneratorHelper
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/// \param[in] slice_list vector of SliceOption objects. Note: If the user passes
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/// {SliceOption(true), SliceOption(true)}, it will return a M x 2 vector, instead of reducing it to
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/// {SliceOption(true)} first to only generate a M x 1 vector.
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/// \return std::vector<std::vector<dsize_t>> 2D vector of generated indices, M x (slice_list).size()
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std::vector<std::vector<dsize_t>> IndexGenerator(const std::vector<SliceOption> &slice_list);
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} // namespace dataset
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_MINDDATA_DATASET_CORE_TENSOR_HELPERS_H_
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