fix cache description
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@ -435,7 +435,8 @@ class Dataset:
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parallel (default=None, the value from the config will be used).
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python_multiprocessing (bool, optional): Parallelize python operations with multiple worker process. This
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option could be beneficial if the python operation is computational heavy (default=False).
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cache (DatasetCache, optional): Tensor cache to use. (default=None which means no cache is used)
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cache (DatasetCache, optional): Tensor cache to use. (default=None which means no cache is used).
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The cache feature is under development and is not recommended.
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Returns:
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MapDataset, dataset after mapping operation.
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@ -1951,7 +1952,9 @@ class MapDataset(DatasetOp):
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in parallel (default=None).
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python_multiprocessing (bool, optional): Parallelize python operations with multiple worker process. This
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option could be beneficial if the python operation is computational heavy (default=False).
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cache (DatasetCache, optional): Tensor cache to use. (default=None which means no cache is used)
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cache (DatasetCache, optional): Tensor cache to use. (default=None which means no cache is used).
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The cache feature is under development and is not recommended.
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Raises:
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ValueError: If len(input_columns) != len(output_columns) and columns_order is not specified.
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@ -2552,7 +2555,8 @@ class ImageFolderDatasetV2(MappableDataset):
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into (default=None).
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shard_id (int, optional): The shard ID within num_shards (default=None). This
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argument should be specified only when num_shards is also specified.
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cache (DatasetCache, optional): Tensor cache to use. (default=None which means no cache is used)
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cache (DatasetCache, optional): Tensor cache to use. (default=None which means no cache is used).
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The cache feature is under development and is not recommended.
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Raises:
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RuntimeError: If sampler and shuffle are specified at the same time.
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@ -3348,7 +3352,8 @@ class TFRecordDataset(SourceDataset):
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argument should be specified only when num_shards is also specified.
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shard_equal_rows (bool): Get equal rows for all shards(default=False). If shard_equal_rows is false, number
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of rows of each shard may be not equal.
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cache (DatasetCache, optional): Tensor cache to use. (default=None which means no cache is used)
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cache (DatasetCache, optional): Tensor cache to use. (default=None which means no cache is used).
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The cache feature is under development and is not recommended.
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Examples:
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>>> import mindspore.dataset as ds
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>>> import mindspore.common.dtype as mstype
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@ -3919,7 +3924,8 @@ class RandomDataset(SourceDataset):
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num_samples (int): number of samples to draw from the total. (default=None, which means all rows)
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num_parallel_workers (int, optional): number of workers to read the data
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(default=None, number set in the config).
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cache (DatasetCache, optional): Tensor cache to use. (default=None which means no cache is used)
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cache (DatasetCache, optional): Tensor cache to use. (default=None which means no cache is used).
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The cache feature is under development and is not recommended.
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shuffle (bool, optional): Whether or not to perform shuffle on the dataset
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(default=None, expected order behavior shown in the table).
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num_shards (int, optional): Number of shards that the dataset should be divided
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@ -130,7 +130,7 @@ def test_cache_map_basic4():
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ds1 = ds1.map(input_columns=["image"], operations=decode_op)
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logger.info("ds1.dataset_size is ", ds1.get_dataset_size())
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shape = ds1.output_shapes()
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logger.info(shape)
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num_iter = 0
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for _ in ds1.create_dict_iterator():
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logger.info("get data from dataset")
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