mindspore.dataset.dataloader.default_collate

mindspore.dataset.dataloader.default_collate(batch)[源代码]

Take in a batch of data and put the elements within the batch into a tensor with an additional outer dimension - batch size.

The exact output type can be a mindspore.Tensor, a Sequence of mindspore.Tensor, a Collection of mindspore.Tensor, or left unchanged, depending on the input type. This is used as the default function for collation when batch_size or batch_sampler is defined in mindspore.dataset.dataloader.DataLoader.

Here is the general input type (based on the type of the element within the batch) to output type mapping:

  • mindspore.Tensor -> mindspore.Tensor (with an added outer dimension batch size)

  • NumPy Arrays -> mindspore.Tensor

  • float -> mindspore.Tensor

  • int -> mindspore.Tensor

  • str -> str (unchanged)

  • bytes -> bytes (unchanged)

  • Mapping[K, V_i] -> Mapping[K, default_collate([V_1, V_2, …])]

  • NamedTuple[V1_i, V2_i, …] -> NamedTuple[default_collate([V1_1, V1_2, …]), default_collate([V2_1, V2_2, …]), …]

  • Sequence[V1_i, V2_i, …] -> Sequence[default_collate([V1_1, V1_2, …]), default_collate([V2_1, V2_2, …]), …]

Parameters

batch – a single batch to be collated