Added helper methods for torch.distributed.boradcast #189
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For the timing abstraction (#146), the `DataloaderSpec` needed two addition functions -- `get_num_samples_in_batch` and `get_num_tokens_in_batch`. It was getting messy to pass around function pointers in a named tuple, so instead converted `DataloaderSpec` from a NamedTuple into a regular class called `DataSpec`. Custom datasets can inherit the base `DataSpec` class and override functionality as needed. Moved the `DataSpec` class to `composer.core`, as the `DataSpec` is now bound directly to the state. #120 will also need this change. Renamed `train_dataloader` and `eval_dataloader` in the trainer and state to `train_data` and `eval_data`, since it encompasses more than the dataloader. This PR implements part 3 and 4 of the timing abstraction (#146). The implementation differs from the GH issue by adding `num_tokens`, `num_samples`, `get_batch_size`, and `get_num_tokens` to the new `DataSpec` rather than the pytorch dataset class.
jbloxham
approved these changes
Jan 3, 2022
Addressed pr comments
…o ravi/ddp_broadcast
coryMosaicML
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Feb 23, 2022
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