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Motivation

ref: open-mmlab/mmpretrain#752
In some situation, we need to use different dataloader settings like samples_per_gpu in train/val/test dataloader.

Modification

Use train_dataloader, val_dataloader and test_dataloader settings in the data field to specify different arguments.

Use cases (Optional)

data = dict(
    samples_per_gpu=64,
    workers_per_gpu=4,
    train=dict(type='xxx', ...),
    val=dict(type='xxx', ...),
    test=dict(type='xxx', ...),
    # Use different batch size during inference.
    val_dataloader=dict(samples_per_gpu=8, workers_per_gpu=2),
    test_dataloader=dict(samples_per_gpu=8, workers_per_gpu=2),
)

Checklist

1. Pre-commit or other linting tools are used to fix the potential lint issues.
2. The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness.
3. If the modification has potential influence on downstream projects, this PR should be tested with downstream projects, like MMDet or MMDet3D.
4. The documentation has been modified accordingly, like docstring or example tutorials.