Class TFRecordDataset
Defined in File datasets.h
Inheritance Relationships
Base Type
public mindspore::dataset::Dataset
(Class Dataset)
Class Documentation
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class TFRecordDataset : public mindspore::dataset::Dataset
A source dataset for reading and parsing datasets stored on disk in TFData format.
Public Functions
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TFRecordDataset(const std::vector<std::vector<char>> &dataset_files, const std::vector<char> &schema, const std::vector<std::vector<char>> &columns_list, int64_t num_samples, ShuffleMode shuffle, int32_t num_shards, int32_t shard_id, bool shard_equal_rows, const std::shared_ptr<DatasetCache> &cache)
Constructor of TFRecordDataset.
- Parameters
dataset_files – [in] List of files to be read to search for a pattern of files. The list will be sorted in a lexicographical order.
schema – [in] Path to schema file.
columns_list – [in] List of columns to be read (Default = {}, read all columns).
num_samples – [in] The number of samples to be included in the dataset (Default = 0 means all samples). If num_samples is 0 and numRows(parsed from schema) does not exist, read the full dataset; If num_samples is 0 and numRows(parsed from schema) is greater than 0, read numRows rows; If both num_samples and numRows(parsed from schema) are greater than 0, read num_samples rows.
shuffle – [in] The mode for shuffling data every epoch. (Default = ShuffleMode::kGlobal) Can be any of: ShuffleMode::kFalse - No shuffling is performed. ShuffleMode::kFiles - Shuffle files only. ShuffleMode::kGlobal - Shuffle both the files and samples.
num_shards – [in] Number of shards that the dataset should be divided into (Default = 1).
shard_id – [in] The shard ID within num_shards. This argument should be specified only when num_shards is also specified (Default = 0).
shard_equal_rows – [in] Get equal rows for all shards (Default = False, number of rows of each shard may be not equal).
cache – [in] Tensor cache to use (default=nullptr which means no cache is used).
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TFRecordDataset(const std::vector<std::vector<char>> &dataset_files, const std::shared_ptr<SchemaObj> &schema, const std::vector<std::vector<char>> &columns_list, int64_t num_samples, ShuffleMode shuffle, int32_t num_shards, int32_t shard_id, bool shard_equal_rows, const std::shared_ptr<DatasetCache> &cache)
Constructor of TFRecordDataset.
Note
Parameter ‘schema’ is shared pointer to Schema object
- Parameters
dataset_files – [in] List of files to be read to search for a pattern of files. The list will be sorted in a lexicographical order.
schema – [in] SchemaObj to set column type, data type and data shape.
columns_list – [in] List of columns to be read (Default = {}, read all columns).
num_samples – [in] The number of samples to be included in the dataset (Default = 0 means all samples). If num_samples is 0 and numRows(parsed from schema) does not exist, read the full dataset; If num_samples is 0 and numRows(parsed from schema) is greater than 0, read numRows rows; If both num_samples and numRows(parsed from schema) are greater than 0, read num_samples rows.
shuffle – [in] The mode for shuffling data every epoch. (Default = ShuffleMode::kGlobal) Can be any of: ShuffleMode::kFalse - No shuffling is performed. ShuffleMode::kFiles - Shuffle files only. ShuffleMode::kGlobal - Shuffle both the files and samples.
num_shards – [in] Number of shards that the dataset should be divided into (Default = 1).
shard_id – [in] The shard ID within num_shards. This argument should be specified only when num_shards is also specified (Default = 0).
shard_equal_rows – [in] Get equal rows for all shards (Default = False, number of rows of each shard may be not equal).
cache – [in] Tensor cache to use (default=nullptr which means no cache is used).
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~TFRecordDataset() override = default
Destructor of TFRecordDataset.
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TFRecordDataset(const std::vector<std::vector<char>> &dataset_files, const std::vector<char> &schema, const std::vector<std::vector<char>> &columns_list, int64_t num_samples, ShuffleMode shuffle, int32_t num_shards, int32_t shard_id, bool shard_equal_rows, const std::shared_ptr<DatasetCache> &cache)