scvi.dataloaders.ConcatDataLoader#

class scvi.dataloaders.ConcatDataLoader(adata_manager, indices_list, shuffle=False, batch_size=128, data_and_attributes=None, drop_last=False, **data_loader_kwargs)[source]#

DataLoader that supports a list of list of indices to load.

Parameters:
  • adata_manager (AnnDataManager) – AnnDataManager object that has been created via setup_anndata.

  • indices_list (list[list[int]]) – List where each element is a list of indices in the adata to load

  • shuffle (bool (default: False)) – Whether the data should be shuffled

  • batch_size (int (default: 128)) – minibatch size to load each iteration

  • data_and_attributes (Optional[dict] (default: None)) – Dictionary with keys representing keys in data registry (adata_manager.data_registry) and value equal to desired numpy loading type (later made into torch tensor). If None, defaults to all registered data.

  • data_loader_kwargs – Keyword arguments for DataLoader

Attributes table#

multiprocessing_context

dataset

batch_size

num_workers

pin_memory

drop_last

timeout

sampler

pin_memory_device

prefetch_factor

Methods table#

check_worker_number_rationality()

Attributes#

ConcatDataLoader.multiprocessing_context[source]#
ConcatDataLoader.dataset: Dataset[T_co]#
ConcatDataLoader.batch_size: Optional[int]#
ConcatDataLoader.num_workers: int#
ConcatDataLoader.pin_memory: bool#
ConcatDataLoader.drop_last: bool#
ConcatDataLoader.timeout: float#
ConcatDataLoader.sampler: Union[Sampler, Iterable]#
ConcatDataLoader.pin_memory_device: str#
ConcatDataLoader.prefetch_factor: Optional[int]#

Methods#

ConcatDataLoader.check_worker_number_rationality()[source]#