composer.datasets.build_streaming_ade20k_dataloader(global_batch_size, remote, *, version=2, local='/tmp/mds-cache/mds-ade20k/', split='train', drop_last=True, shuffle=True, base_size=512, min_resize_scale=0.5, max_resize_scale=2.0, final_size=512, ignore_background=True, **dataloader_kwargs)[source]#

Build an ADE20k streaming dataset.

  • global_batch_size (int) โ€“ Global batch size.

  • remote (str) โ€“ Remote directory (S3 or local filesystem) where dataset is stored.

  • version (int) โ€“ Which version of streaming to use. Default: 2.

  • local (str) โ€“ Local filesystem directory where dataset is cached during operation. Default: '/tmp/mds-cache/mds-ade20k/`.

  • split (str) โ€“ The dataset split to use, either โ€˜trainโ€™ or โ€˜valโ€™. Default: 'train`.

  • base_size (int) โ€“ Initial size of the image and target before other augmentations. Default: 512.

  • min_resize_scale (float) โ€“ The minimum value the samples can be rescaled. Default: 0.5.

  • max_resize_scale (float) โ€“ The maximum value the samples can be rescaled. Default: 2.0.

  • final_size (int) โ€“ The final size of the image and target. Default: 512.

  • ignore_background (bool) โ€“ If true, ignore the background class when calculating the training loss. Default: true.

  • **dataloader_kwargs (Dict[str, Any]) โ€“ Additional settings for the dataloader (e.g. num_workers, etc.)