torch.nn.utils.prune.identity

torch.nn.utils.prune.identity(module, name)

Applies pruning reparametrization to the tensor corresponding to the parameter called name in module without actually pruning any units. Modifies module in place (and also return the modified module) by:

1. adding a named buffer called name+'_mask' corresponding to the binary mask applied to the parameter name by the pruning method.

2. replacing the parameter name by its pruned version, while the original (unpruned) parameter is stored in a new parameter named name+'_orig'.

Note

The mask is a tensor of ones.

Parameters:

• module (nn.Module) – module containing the tensor to prune.

• name (str) – parameter name within module on which pruning will act.

Returns:

modified (i.e. pruned) version of the input module

Return type:

module (nn.Module)

Examples

>>> m = prune.identity(nn.Linear(2, 3), 'bias')
>>> print(m.bias_mask)
tensor([1., 1., 1.])