Lixia Chen
5 years ago
parent
4aed2bf9ef
commit
6ae88c3987
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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 <utility>
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#include "dataset/core/tensor_row.h"
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namespace py = pybind11;
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namespace mindspore {
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namespace dataset {
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TensorRow::TensorRow() noexcept : id_(kDefaultRowId) {}
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TensorRow::TensorRow(size_type n, TensorRow::value_type t) noexcept : id_(kDefaultRowId), row_(n, t) {}
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TensorRow::TensorRow(const TensorRow::vector_type &v) : id_(kDefaultRowId), row_(v) {}
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TensorRow::TensorRow(row_id_type id, const std::initializer_list<value_type> &lst) : id_(id), row_(lst) {}
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TensorRow::TensorRow(const TensorRow &tr) : id_(tr.id_), row_(tr.row_) {}
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TensorRow &TensorRow::operator=(const TensorRow &tr) {
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if (this == &tr) {
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return *this;
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}
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row_ = tr.row_;
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id_ = tr.id_;
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return *this;
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}
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TensorRow &TensorRow::operator=(const std::initializer_list<TensorRow::value_type> &lst) {
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row_ = lst;
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return *this;
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}
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TensorRow::TensorRow(TensorRow::vector_type &&v) noexcept : id_(kDefaultRowId), row_(std::move(v)) {}
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TensorRow::TensorRow(row_id_type id, std::initializer_list<value_type> &&lst) noexcept
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: id_(id), row_(std::move(lst)) {}
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TensorRow::TensorRow(TensorRow &&tr) noexcept {
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id_ = tr.id_;
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row_ = std::move(tr.row_);
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}
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TensorRow &TensorRow::operator=(TensorRow &&tr) noexcept {
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if (this == &tr) {
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return *this;
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}
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row_ = std::move(tr.row_);
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id_ = tr.id_;
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tr.id_ = kDefaultRowId;
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return *this;
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}
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TensorRow &TensorRow::operator=(std::initializer_list<TensorRow::value_type> &&lst) noexcept {
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row_ = std::move(lst);
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return *this;
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}
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} // namespace dataset
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} // namespace mindspore
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@ -0,0 +1,131 @@
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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 DATASET_CORE_TENSOR_ROW_H_
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#define DATASET_CORE_TENSOR_ROW_H_
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#include <deque>
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#include <memory>
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#include <vector>
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#include "dataset/core/tensor.h"
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namespace mindspore {
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namespace dataset {
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class TensorRow; // A set of Tensor pointers with an id
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using TensorTable = std::vector<TensorRow>; // The table of tensors is a vector of rows
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using TensorQTable = std::deque<TensorRow>; // A different flavour of tensor table, this one has queue functionality
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class TensorRow {
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public:
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static constexpr row_id_type kDefaultRowId = -1; // Default row id
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// Type definitions
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typedef dsize_t size_type;
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typedef std::shared_ptr<Tensor> value_type;
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typedef std::shared_ptr<Tensor> &reference;
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typedef const std::shared_ptr<Tensor> &const_reference;
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typedef std::vector<std::shared_ptr<Tensor>> vector_type;
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typedef std::vector<std::shared_ptr<Tensor>>::iterator iterator;
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typedef std::vector<std::shared_ptr<Tensor>>::const_iterator const_iterator;
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TensorRow() noexcept;
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TensorRow(size_type n, value_type t) noexcept;
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// Copy Constructors
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explicit TensorRow(const vector_type &v);
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TensorRow(row_id_type id, const std::initializer_list<value_type> &lst);
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TensorRow(const TensorRow &tr);
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TensorRow &operator=(const TensorRow &tr);
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TensorRow &operator=(const std::initializer_list<value_type> &lst);
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// Move Constructors
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explicit TensorRow(vector_type &&v) noexcept;
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TensorRow(row_id_type id, std::initializer_list<value_type> &&lst) noexcept;
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TensorRow(TensorRow &&tr) noexcept;
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TensorRow &operator=(TensorRow &&tr) noexcept;
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TensorRow &operator=(std::initializer_list<value_type> &&lst) noexcept;
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// Destructor
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~TensorRow() = default;
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// Functions to fetch/set id/vector
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row_id_type getId() const { return id_; }
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void setId(row_id_type id) { id_ = id; }
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const vector_type &getRow() const { return row_; }
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// Wrapper functions to support vector operations
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void emplace_back(value_type t) { row_.emplace_back(t); }
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void push_back(value_type t) { row_.push_back(t); }
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void clear() noexcept { row_.clear(); }
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size_type size() const noexcept { return row_.size(); }
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void reserve(size_type size) { row_.reserve(size); }
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void resize(size_type size) { row_.resize(size); }
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bool empty() { return row_.empty(); }
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void insert(iterator position, iterator first, iterator last) { row_.insert(position, first, last); }
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// Wrapper functions to support vector element access
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reference at(size_type index) { return row_.at(index); }
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const_reference at(size_type index) const { return row_.at(index); }
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reference front() { return row_.front(); }
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const_reference front() const { return row_.front(); }
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reference back() { return row_.back(); }
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const_reference back() const { return row_.back(); }
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reference operator[](size_type index) { return row_[index]; }
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const_reference operator[](size_type index) const { return row_[index]; }
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// Wrapper functions to support vector iteration
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iterator begin() { return row_.begin(); }
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const_iterator begin() const { return row_.begin(); }
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iterator end() { return row_.end(); }
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const_iterator end() const { return row_.end(); }
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protected:
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row_id_type id_;
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std::vector<std::shared_ptr<Tensor>> row_;
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};
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} // namespace dataset
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} // namespace mindspore
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#endif // DATASET_CORE_TENSOR_ROW_H_
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