tensorplay.ao.pruning.random_structured

tensorplay.ao.pruning.random_structured(module: Module, name: str, amount: int | float, dim: int) → Module[source]

Prune module[name] by removing random channels along dim.

Removes amount (currently unpruned) channels chosen uniformly at random. Modifies the module in place (and also returns it) by:

1. adding a named buffer called name + '_mask' holding the binary mask applied to the parameter name;

2. replacing the parameter name by its masked version, while the original (unmasked) values are stored in a new parameter named name + '_orig'.

Parameters:

• module – module containing the tensor to prune.

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

• amount – quantity of channels to prune. A float in [0, 1] denotes the fraction of channels to prune; an int denotes the absolute number of channels to prune.

• dim – axis along which channels are defined.

Returns:

The modified (i.e. pruned) module.

Examples

>>> # xdoctest: +SKIP
>>> m = random_structured(nn.Linear(5, 3), "weight", amount=3, dim=1)
>>> columns_pruned = int(sum(tensorplay.sum(m.weight, dim=0) == 0))
>>> print(columns_pruned)
3