a d @sddlmZmZmZddlmZgdZdejejeeedddZ eejeeejdd d Z ejeeeefd d d Z GdddejZ dS))AnyDictOptional)nn) module_to_fqn fqn_to_moduleget_arg_info_from_tensor_fqn FakeSparsity)modelmoduleprefixreturncCsH||ur dS|D].\}}t||d}t|tr|||SqdS)zS Returns the fqn for a module or None if module not a descendent of model. r .N)Znamed_childrenr isinstancestr)r r r namechildZfqnrj/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/torch/ao/pruning/sparsifier/utils.pyr s  r)r pathrcCs(|dkr$|dD]}t||d}q|S)z Given an fqn, returns the corresponding module or tensor or None if the fqn given by `path` doesn't correspond to anything. Similar to model.get_submodule(path) but works for tensors. r rN)splitgetattr)r rrrrrrsr)r tensor_fqnrcCs@|dd}|dt| d|v}t||}||||dS)zX Uses tensor_fqn to obtain a dict containing module_fqn, module and tensor_name rN) module_fqnr tensor_namer)rlenr)r rrrr rrrr%s rcs0eZdZdZfddZddZddZZS)r a:Parametrization for the weights. Should be attached to the 'weight' or any other parmeter that requires a mask applied to it. Note:: Once the mask is passed, the variable should not change the id. The contents of the mask can change, but the mask reference itself should not. cst|d|dS)Nmask)super__init__Zregister_buffer)selfr __class__rrr Ds zFakeSparsity.__init__cCs|jj|jksJ|j|SN)rshape)r!xrrrforwardHszFakeSparsity.forwardcOsiSr$r)r!argskwargsrrr state_dictLszFakeSparsity.state_dict)__name__ __module__ __qualname____doc__r r'r* __classcell__rrr"rr :s r N)r ) typingrrrZtorchr__all__Modulerrrrr rrrrs