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1. Support to include in sparse_parameter_list an user-supplied custom layer type and its parameter name. This is useful when users have their own implementation of nn.Linear or nn.Conv2D. For example, huggingface repo has a custom implementation of nn.Linear called LinearActivation.
2. Print info of layers in the model that are not pruned.

Merge pull request #917 from a-maci/master

Fixing the case when grads are None

Fixing mask multiplication with grad tensors

Grads can be None type. Adding this fix to skip multiplication with masks if this is the case.

Updating my repo

Fixed weight init for fused weight matrices in fused MHA by adding correct gain factor

Fixed variable name

* [sync BN]

support non-uniform batch size across process group.

TODO: test should be added once cleaned up.

* updating unit tests

* new unit tests for different inputs

* cleaning

* Only attempt to patch Tensor methods if defined

* syntax
Co-authored-by: Michael Carilli <mcarilli@nvidia.com>

add unit tests for FusedLAMB optimizer

2d masking and sparsity

Minor edit

Importance and usage is 2d masking

Update softmax.h

Fixing NULL stream launch in dispatch_additive_masked_softmax

add streaming support for softmax kernels

Sparsity

Co-authored-by: Michael Carilli <mcarilli@nvidia.com>

Remove distributed lamb from __init__.py

Distributed lamb optimizer