mindspore.dataset.SubsetRandomSampler

class mindspore.dataset.SubsetRandomSampler(indices, num_samples=None)[source]

Samples the elements randomly from a sequence of indices.

Parameters

indices (Any iterable python object but string) – A sequence of indices.
num_samples (int, optional) – Number of elements to sample (default=None, all elements).

Examples

>>> indices = [0, 1, 2, 3, 7, 88, 119]
>>>
>>> # create a SubsetRandomSampler, will sample from the provided indices
>>> sampler = ds.SubsetRandomSampler(indices)
>>> data = ds.ImageFolderDataset(image_folder_dataset_dir, num_parallel_workers=8, sampler=sampler)

Raises

TypeError – If type of indices element is not a number.
TypeError – If num_samples is not an integer value.
RuntimeError – If num_samples is a negative value.

add_child(sampler)

Add a sub-sampler for given sampler. The sub-sampler will receive all data from the output of parent sampler and apply its sample logic to return new samples.

Parameters: sampler (Sampler) – Object used to choose samples from the dataset. Only builtin samplers(DistributedSampler, PKSampler, RandomSampler, SequentialSampler, SubsetRandomSampler, WeightedRandomSampler) are supported.

Examples

>>> sampler = ds.SequentialSampler(start_index=0, num_samples=3)
>>> sampler.add_child(ds.RandomSampler(num_samples=2))
>>> dataset = ds.Cifar10Dataset(cifar10_dataset_dir, sampler=sampler)

get_child(): add a child sampler

parse()[source]: Parse the sampler.

parse_child(): Parse the child sampler.

parse_child_for_minddataset(): Parse the child sampler for MindRecord.

parse_for_minddataset()[source]: Parse the sampler for MindRecord.