GitLab

Rename --batch-size to --micro-batch-size and drop in-minibatch from --num-micro-batches-in-minibatch

Refactor code according to Jared's comments: move pipelining and non-pipelining training loops into separate methods

Also, use mpu.get_*_model_parallel_size() instead of args.*_model_parallel_size

Allocate tensor in `communicate()` method directly on GPU (instead of allocating on CPU and then moving to GPU)

Prevents data_loader from running out of training examples

Make sure all forward and backward operations are accounted for

Also includes following changes for inter-layer model-parallel implementation:
- Refactoring of model implementations
- Training loop changes to support inter-layer communication using `ring_exchange`
- New groups for inter-layer communication
- Checkpoint changes
- Command line arguments