Promote Supermask out of prototype

[jcaip]

This PR promotes Supermask and block sparsity from prototype -> torchao.sparsity, instead of the apply_supermask function which was previously closely coupled with SAM.

It adds a new public API for SupermaskLinear, which users can use to add Supermask to their models for training with

sparsify_(model, lambda x: SupermaskLinear.from_linear(x, block_size=64, sparsity_level=0.9)

To accelerate for inference, we convert the SupermaskLinear model back into a nn.Linear, which simplifies the Supermask logic:

sparsify_(model, lambda x: SupermaskLinear.to_linear(x, sparsity_level=0.9)

bc-breaking

The previous prototype APIs, torchao.sparsity.prototype.superblock.supermask and torchao.prototype.sparsity.superblock.supermask have been deprecated.

You can use torchao.sparsity.supermask instead.

[pytorch-bot]

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