fix: Using batchsize of batch_sampler when using BatchSampler

[bigd4]

What does this PR do?

Fixes #21122

When DataLoader is defined with DataLoader(dataset, batch_sampler=BatchSampler(...)), the batch_size and drop_last will be default values (1 and False). So _dataloader_init_kwargs_resolve_sampler may return wrong parameters.

Changes

return batch_sampler.batch_size and batch_sampler.drop_last if batch_sampler is BatchSampler.

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📚 Documentation preview 📚: https://pytorch-lightning--21566.org.readthedocs.build/en/21566/

[bigd4]

@deependujha
The tests fail becase pytorch-lightning/tests/tests_pytorch/trainer/connectors/test_data_connector.py line 198-200. The missing value are ['batch_sampler', 'batch_size', 'drop_last', 'sampler', 'shuffle'] instead of ['batch_sampler', 'sampler', 'shuffle'].

    loader = TestDataLoader(ds)
    sampler = SequentialSampler(ds)
    match = escape("missing arguments are ['batch_sampler', 'sampler', 'shuffle']")
    with pytest.raises(MisconfigurationException, match=match):
        _update_dataloader(loader, sampler, mode="fit")
    match = escape("missing arguments are ['batch_sampler', 'batch_size', 'drop_last', 'sampler', 'shuffle']")
    with pytest.raises(MisconfigurationException, match=match):
        _update_dataloader(loader, sampler, mode="predict")

I dont know if I should change match = escape("missing arguments are ['batch_sampler', 'sampler', 'shuffle']") or any other ideas?