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1 /**
2  * Copyright 2020 Huawei Technologies Co., Ltd
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  * http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16 
17 #ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_BATCH_NODE_H_
18 #define MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_BATCH_NODE_H_
19 
20 #include <map>
21 #include <memory>
22 #include <string>
23 #include <utility>
24 #include <vector>
25 
26 #include "minddata/dataset/engine/ir/datasetops/dataset_node.h"
27 #include "minddata/dataset/engine/opt/pass.h"
28 
29 namespace mindspore {
30 namespace dataset {
31 
32 class BatchNode : public DatasetNode {
33  public:
34 #ifdef ENABLE_PYTHON
35   /// \brief Constructor #1, for Python API to create a BatchNode
36   BatchNode(std::shared_ptr<DatasetNode> child, int32_t batch_size, bool drop_remainder, bool pad,
37             const std::vector<std::string> &in_col_names, const std::vector<std::string> &out_col_names,
38             const std::vector<std::string> &col_order, py::function batch_size_func, py::function batch_map_func,
39             std::map<std::string, std::pair<TensorShape, std::shared_ptr<Tensor>>> pad_map);
40 #endif
41 
42   /// \brief Constructor #2 for C++ API to create a BatchNode
43   BatchNode(std::shared_ptr<DatasetNode> child, int32_t batch_size, bool drop_remainder);
44 
45   /// \brief Destructor
46   ~BatchNode() = default;
47 
48   /// \brief Node name getter
49   /// \return Name of the current node
Name()50   std::string Name() const override { return kBatchNode; }
51 
52   /// \brief Print the description
53   /// \param out - The output stream to write output to
54   void Print(std::ostream &out) const override;
55 
56   /// \brief Copy the node to a new object
57   /// \return A shared pointer to the new copy
58   std::shared_ptr<DatasetNode> Copy() override;
59 
60   /// \brief a base class override function to create the required runtime dataset op objects for this class
61   /// \param node_ops - A vector containing shared pointer to the Dataset Ops that this object will create
62   /// \return Status Status::OK() if build successfully
63   Status Build(std::vector<std::shared_ptr<DatasetOp>> *const node_ops) override;
64 
65   /// \brief Parameters validation
66   /// \return Status Status::OK() if all the parameters are valid
67   Status ValidateParams() override;
68 
69   /// \brief Base-class override for GetDatasetSize
70   /// \param[in] size_getter Shared pointer to DatasetSizeGetter
71   /// \param[in] estimate This is only supported by some of the ops and it's used to speed up the process of getting
72   ///     dataset size at the expense of accuracy.
73   /// \param[out] dataset_size the size of the dataset
74   /// \return Status of the function
75   Status GetDatasetSize(const std::shared_ptr<DatasetSizeGetter> &size_getter, bool estimate,
76                         int64_t *dataset_size) override;
77 
78   /// \brief Base-class override for accepting IRNodePass visitor
79   /// \param[in] p The node to visit
80   /// \param[out] modified Indicator if the node was modified
81   /// \return Status of the node visit
82   Status Accept(IRNodePass *const p, bool *const modified) override;
83 
84   /// \brief Base-class override for accepting IRNodePass visitor
85   /// \param[in] p The node to visit
86   /// \param[out] modified Indicator if the node was modified
87   /// \return Status of the node visit
88   Status AcceptAfter(IRNodePass *const p, bool *const modified) override;
89 
90   /// \brief Getter functions
BatchSize()91   int32_t BatchSize() const { return batch_size_; }
DropRemainder()92   bool DropRemainder() const { return drop_remainder_; }
93 #ifdef ENABLE_PYTHON
Pad()94   bool Pad() const { return pad_; }
InColNames()95   const std::vector<std::string> &InColNames() const { return in_col_names_; }
OutColNames()96   const std::vector<std::string> &OutColNames() const { return out_col_names_; }
ColOrder()97   const std::vector<std::string> &ColOrder() const { return col_order_; }
BatchSizeFunc()98   const py::function &BatchSizeFunc() const { return batch_size_func_; }
BatchMapFunc()99   const py::function &BatchMapFunc() const { return batch_map_func_; }
PadMap()100   const std::map<std::string, std::pair<TensorShape, std::shared_ptr<Tensor>>> &PadMap() const { return pad_map_; }
101 #endif
102 
103   /// \brief Get the arguments of node
104   /// \param[out] out_json JSON string of all attributes
105   /// \return Status of the function
106   Status to_json(nlohmann::json *out_json) override;
107 
108   /// \brief Function for read dataset operation from json
109   /// \param[in] json_obj The JSON object to be deserialized
110   /// \param[in] ds dataset node constructed
111   /// \param[out] result Deserialized dataset after the operation
112   /// \return Status The status code returned
113   static Status from_json(nlohmann::json json_obj, std::shared_ptr<DatasetNode> ds,
114                           std::shared_ptr<DatasetNode> *result);
115 
116  private:
117   int32_t batch_size_;
118   bool drop_remainder_;
119   bool pad_;
120   std::vector<std::string> in_col_names_;
121   std::vector<std::string> out_col_names_;
122   std::vector<std::string> col_order_;
123 #ifdef ENABLE_PYTHON
124   py::function batch_size_func_;
125   py::function batch_map_func_;
126 #endif
127   std::map<std::string, std::pair<TensorShape, std::shared_ptr<Tensor>>> pad_map_;
128 };
129 
130 }  // namespace dataset
131 }  // namespace mindspore
132 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_BATCH_NODE_H_
133