forked from mindspore-Ecosystem/mindspore
fix dataset api description
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@ -556,7 +556,7 @@ class Dataset:
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Note:
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If device is Ascend, features of data will be transferred one by one. The limitation
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of data transferation per time is 256M.
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of data transmission per time is 256M.
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Return:
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TransferDataset, dataset for transferring.
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@ -572,7 +572,7 @@ class Dataset:
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Note:
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If device is Ascend, features of data will be transferred one by one. The limitation
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of data transferation per time is 256M.
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of data transmission per time is 256M.
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Returns:
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TransferDataset, dataset for transferring.
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@ -1897,7 +1897,7 @@ class GeneratorDataset(SourceDataset):
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>>> for i in range(maxid):
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>>> yield (np.array([i]), np.array([[i, i + 1], [i + 2, i + 3]]))
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>>> # create multi_column_generator_dataset with GeneratorMC and column names "col1" and "col2"
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>>> multi_column_generator_dataset = de.GeneratorDataset(generator_mc, ["col1, col2"])
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>>> multi_column_generator_dataset = de.GeneratorDataset(generator_mc, ["col1", "col2"])
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>>> # 3) Iterable dataset as iterable input
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>>> class MyIterable():
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>>> def __iter__(self):
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@ -112,8 +112,7 @@ class RandomSampler():
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Args:
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replacement (bool, optional): If True, put the sample ID back for the next draw (default=False).
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num_samples (int, optional): Number of elements to sample (default=None, all elements). This
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argument should be specified only when 'replacement' is "True".
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num_samples (int, optional): Number of elements to sample (default=None, all elements).
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Examples:
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>>> import mindspore.dataset as ds
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@ -362,6 +362,8 @@ class Model:
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If dataset_sink_mode is True, epoch of training should be equal to the count of repeat
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operation in dataset processing. Otherwise, errors could occur since the amount of data
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is not the amount training requires.
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If dataset_sink_mode is True, data will be sent to device. If device is Ascend, features
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of data will be transferred one by one. The limitation of data transmission per time is 256M.
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Args:
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epoch (int): Total number of iterations on the data.
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@ -485,6 +487,8 @@ class Model:
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Note:
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CPU is not supported when dataset_sink_mode is true.
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If dataset_sink_mode is True, data will be sent to device. If device is Ascend, features
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of data will be transferred one by one. The limitation of data transmission per time is 256M.
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Args:
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valid_dataset (Dataset): Dataset to evaluate the model.
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