diff --git a/mindspore/dataset/engine/datasets.py b/mindspore/dataset/engine/datasets.py index 2fafd6249e..d2e8679c7a 100644 --- a/mindspore/dataset/engine/datasets.py +++ b/mindspore/dataset/engine/datasets.py @@ -3169,8 +3169,8 @@ class GeneratorDataset(MappableDataset): num_parallel_workers (int, optional): Number of subprocesses used to fetch the dataset in parallel (default=1). shuffle (bool, optional): Whether or not to perform shuffle on the dataset. Random accessible input is required. (default=None, expected order behavior shown in the table). - sampler (Union[Sampler, Iterable], optional): Object used to choose samples from the dataset. Random accessible input is - required (default=None, expected order behavior shown in the table). + sampler (Union[Sampler, Iterable], optional): Object used to choose samples from the dataset. Random accessible + input is required (default=None, expected order behavior shown in the table). num_shards (int, optional): Number of shards that the dataset should be divided into (default=None). When this argument is specified, 'num_samples' will not effect. Random accessible input is required. shard_id (int, optional): The shard ID within num_shards (default=None). This argument should be specified only @@ -3322,8 +3322,8 @@ class TFRecordDataset(SourceDataset): A source dataset that reads and parses datasets stored on disk in TFData format. Args: - dataset_files (Union[str, list[str]]): String or list of files to be read or glob strings to search for a pattern of - files. The list will be sorted in a lexicographical order. + dataset_files (Union[str, list[str]]): String or list of files to be read or glob strings to search for a + pattern of files. The list will be sorted in a lexicographical order. schema (Union[str, Schema], optional): Path to the json schema file or schema object (default=None). If the schema is not provided, the meta data from the TFData file is considered the schema. columns_list (list[str], optional): List of columns to be read (default=None, read all columns) @@ -3333,7 +3333,8 @@ class TFRecordDataset(SourceDataset): If both num_samples and numRows(parsed from schema) are greater than 0, read num_samples rows. num_parallel_workers (int, optional): number of workers to read the data (default=None, number set in the config). - shuffle (Union[bool, Shuffle level], optional): perform reshuffling of the data every epoch (default=Shuffle.GLOBAL). + shuffle (Union[bool, Shuffle level], optional): perform reshuffling of the data every epoch + (default=Shuffle.GLOBAL). If shuffle is False, no shuffling will be performed; If shuffle is True, the behavior is the same as setting shuffle to be Shuffle.GLOBAL Otherwise, there are two levels of shuffling: @@ -4710,7 +4711,8 @@ class CLUEDataset(SourceDataset): num_samples (int, optional): number of samples(rows) to read (default=None, reads the full dataset). num_parallel_workers (int, optional): number of workers to read the data (default=None, number set in the config). - shuffle (Union[bool, Shuffle level], optional): perform reshuffling of the data every epoch (default=Shuffle.GLOBAL). + shuffle (Union[bool, Shuffle level], optional): perform reshuffling of the data every epoch + (default=Shuffle.GLOBAL). If shuffle is False, no shuffling will be performed; If shuffle is True, the behavior is the same as setting shuffle to be Shuffle.GLOBAL Otherwise, there are two levels of shuffling: @@ -4926,7 +4928,8 @@ class CSVDataset(SourceDataset): num_samples (int, optional): number of samples(rows) to read (default=None, reads the full dataset). num_parallel_workers (int, optional): number of workers to read the data (default=None, number set in the config). - shuffle (Union[bool, Shuffle level], optional): perform reshuffling of the data every epoch (default=Shuffle.GLOBAL). + shuffle (Union[bool, Shuffle level], optional): perform reshuffling of the data every epoch + (default=Shuffle.GLOBAL). If shuffle is False, no shuffling will be performed; If shuffle is True, the behavior is the same as setting shuffle to be Shuffle.GLOBAL Otherwise, there are two levels of shuffling: @@ -5018,12 +5021,13 @@ class TextFileDataset(SourceDataset): The generated dataset has one columns ['text']. Args: - dataset_files (Union[str, list[str]]): String or list of files to be read or glob strings to search for a pattern of - files. The list will be sorted in a lexicographical order. + dataset_files (Union[str, list[str]]): String or list of files to be read or glob strings to search for a + pattern of files. The list will be sorted in a lexicographical order. num_samples (int, optional): number of samples(rows) to read (default=None, reads the full dataset). num_parallel_workers (int, optional): number of workers to read the data (default=None, number set in the config). - shuffle (Union[bool, Shuffle level], optional): perform reshuffling of the data every epoch (default=Shuffle.GLOBAL). + shuffle (Union[bool, Shuffle level], optional): perform reshuffling of the data every epoch + (default=Shuffle.GLOBAL). If shuffle is False, no shuffling will be performed; If shuffle is True, the behavior is the same as setting shuffle to be Shuffle.GLOBAL Otherwise, there are two levels of shuffling: @@ -5204,17 +5208,17 @@ class NumpySlicesDataset(GeneratorDataset): - not allowed Args: - data (Union[list, tuple, dict]) Input of Given data, supported data type includes list, tuple, dict and other numpy - format. Input data will be sliced in first dimension and generate many rows, large data is not recommend to - load in this way as data is loading into memory. + data (Union[list, tuple, dict]) Input of Given data, supported data type includes list, tuple, dict and other + numpy format. Input data will be sliced in first dimension and generate many rows, large data is not + recommend to load in this way as data is loading into memory. column_names (list[str], optional): List of column names of the dataset (default=None). If column_names not provided, when data is dict, column_names will be its key, otherwise it will be like column_1, column_2 ... num_samples (int, optional): The number of samples to be included in the dataset (default=None, all images). num_parallel_workers (int, optional): Number of subprocesses used to fetch the dataset in parallel (default=1). shuffle (bool, optional): Whether or not to perform shuffle on the dataset. Random accessible input is required. (default=None, expected order behavior shown in the table). - sampler (Union[Sampler, Iterable], optional): Object used to choose samples from the dataset. Random accessible input is - required (default=None, expected order behavior shown in the table). + sampler (Union[Sampler, Iterable], optional): Object used to choose samples from the dataset. Random accessible + input is required (default=None, expected order behavior shown in the table). num_shards (int, optional): Number of shards that the dataset should be divided into (default=None). When this argument is specified, 'num_samples' will not effect. Random accessible input is required. shard_id (int, optional): The shard ID within num_shards (default=None). This argument should be specified only @@ -5255,8 +5259,8 @@ class BuildVocabDataset(DatasetOp): Args: vocab(Vocab): text.vocab object. - columns(Union[str, list], optional): column names to get words from. It can be a list of column names (Default is - None, all columns are used, return error if any column isn't string). + columns(Union[str, list], optional): column names to get words from. It can be a list of column names (Default + is None, all columns are used, return error if any column isn't string). freq_range(tuple, optional): A tuple of integers (min_frequency, max_frequency). Words within the frequency range would be kept. 0 <= min_frequency <= max_frequency <= total_words. min_frequency/max_frequency can be None, which corresponds to 0/total_words separately (default=None, all words are included). diff --git a/mindspore/dataset/transforms/vision/c_transforms.py b/mindspore/dataset/transforms/vision/c_transforms.py index 7e14d2ea48..9a07c58a19 100644 --- a/mindspore/dataset/transforms/vision/c_transforms.py +++ b/mindspore/dataset/transforms/vision/c_transforms.py @@ -552,7 +552,8 @@ class RandomRotation(cde.RandomRotationOp): Note that the expand flag assumes rotation around the center and no translation. center (tuple, optional): Optional center of rotation (a 2-tuple) (default=None). Origin is the top left corner. None sets to the center of the image. - fill_value (Union[int, tuple], optional): Optional fill color for the area outside the rotated image (default=0). + fill_value (Union[int, tuple], optional): Optional fill color for the area outside the rotated image + (default=0). If it is a 3-tuple, it is used for R, G, B channels respectively. If it is an int, it is used for all RGB channels. """