GitLab

fix the guard to fall back to the baseline fused layer norm kernel

Persisten ln: move the guard for supported hidden sizes to layer norm module

consider the case of pipeline-model prallelism

clean up arugments

argument naming cleanup

update readme and examples

- Accumulate encoder hidden state gradient to handle skip connection
- Correctly compute the number of layers in encoder / decoder for T5 model
- Ensure e weights are initialized the same way in embeddings
- Synchronize embedding gradients across encoder and decoder for T5 model
- Support for checkpoint loading and saving

- Split a model's computation into multiple virtual stages as needed,
and schedule communication correctly between these virtual stages
- Move schedule code into `schedules.py` and communication code into
`p2p_communication.py`
- Use hyphens instead of spaces in all time logging for consistency
- Factor out code in megatron/training.py into helper functions
- Refactor evaluate() function: make it use forward_backward_schedule
functions

Move rearranging query_key_value and key_value values in old checkpoints to when the checkpoint is loaded instead of runtime..

Add the option for fp32 residual connection (fp32 residual connection machinery still needs to be added)

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

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