mindspore.dataset.dataloader.DataLoader
- class mindspore.dataset.dataloader.DataLoader(dataset, batch_size=1, shuffle=None, sampler=None, batch_sampler=None, num_workers=0, collate_fn=None, pin_memory=False, drop_last=False, timeout=0., worker_init_fn=None, multiprocessing_context=None, generator=None, *, prefetch_factor=None, persistent_workers=False, in_order=True)[source]
Data loader provides an iterator over the given dataset.
It supports map style and iterable style dataset with single or multi-process loading.
- Parameters
dataset (Dataset) – The dataset to load data from.
batch_size (Union[int, None], optional) – The number of samples per mini-batch. If
None
, will not batch. Default:1
.shuffle (Union[bool, None], optional) – Whether to shuffle the dataset. Default:
None
, not shuffle.sampler (Union[Sampler, Iterable, None], optional) – The sampler to use. Default:
None
, useSequentialSampler
if shuffle isFalse
, or useRandomSampler
.batch_sampler (Union[Sampler[List], Iterable[List], None], optional) – The batch sampler to use. Default:
None
,generate internalBatchSampler
if batch_size is notNone
.num_workers (int, optional) – The number of workers for loading. Default:
0
, load in main process.collate_fn (Union[_CollateFnType, None], optional) – The collate function to use. Default:
None
, use default collate function.pin_memory (bool, optional) – Whether to copy data into pinned memory. Default:
False
.drop_last (bool, optional) – Whether to drop the last incomplete batch. Default:
False
.timeout (float, optional) – The timeout for waiting the worker to process the data. Default:
0.
, wait forever.worker_init_fn (Union[Callable[[int], None], None], optional) – The worker init function to use. Default:
None
, do nothing.multiprocessing_context (Union[multiprocessing.context.BaseContext, str, None], optional) – The multiprocessing context to use. Default:
None
, usemindspore.multiprocessing
.generator (Union[Generator, None], optional) – The generator to use. Default:
None
, use default generator.
- Keyword Arguments
prefetch_factor (Union[int, None], optional) – The prefetch factor. Default:
None
, use2
when num_workers is greater than0
.persistent_workers (bool, optional) – Whether to keep the worker alive after iteration. Default:
False
.in_order (bool, optional) – Whether to keep the order of the data in multi-process loading. Default:
True
.