CustomFromMask

class tensorplay.ao.pruning.CustomFromMask(mask: Tensor)[source]

Zero out exactly the units designated by a caller-supplied mask.

Parameters:

mask – binary mask whose zeros mark the units to prune.

classmethod apply(module: Module, name: str, mask: Tensor) → BasePruningMethod[source]

Install a user-provided mask for module[name].

Parameters:

• module – module containing the tensor to prune.

• name – parameter name within module on which pruning acts.

• mask – binary mask to be applied to the parameter.

apply_mask(module: Module) → Tensor

Return the pruned version of the tensor held by module.

Fetches the mask and the original values from the module and returns their elementwise product.

Parameters:

module – module holding the pruned tensor.

Returns:

The product of the mask and the original values.

prune(t: Tensor, default_mask: Tensor | None = None, importance_scores: Tensor | None = None) → Tensor

Return a pruned copy of the input tensor t.

Applies the rule implemented by compute_mask() without any module-side reparameterization.

Parameters:

• t – tensor to prune (same shape as default_mask).

• importance_scores – tensor of importance scores with the same shape as t; each entry ranks the corresponding element of t. When unspecified, t itself is used.

• default_mask – mask from a previous pruning iteration, if any. Pruning must respect the entries it already zeroes. When unspecified, a mask of ones is used.

Returns:

The pruned version of t.

remove(module: Module) → None

Make the current pruning of module permanent.

The pruned values remain pruned: the product of mask and original values is written back into the parameter name, and the auxiliary parameter name + '_orig' and buffer name + '_mask' are dropped.

Note

Pruning itself is NOT undone or reversed!