o I h @s ddlmZddlmZmZddlmZddlmZm Z gdZ dej de ej de fd d Zd ej d ee ej e ej fdej fd dZ ddej dej dedeefddZdeej dedeej fddZdej dedeeeffddZGdddej ZdS))chain)AnyOptional)nn)is_parametrizedtype_before_parametrizations)module_contains_param swap_module module_to_fqn fqn_to_moduleget_arg_info_from_tensor_fqn FakeSparsitymoduleparametrizationreturncs(t|rtfdd|jDSdS)Nc3s*|]\}}tfdd|DVqdS)c3s|]}t|VqdSN) isinstance).0paramrU/var/www/vscode/kcb/lib/python3.10/site-packages/torch/ao/pruning/sparsifier/utils.py sz2module_contains_param...N)any)rkey param_listrrrrs  z(module_contains_param..F)rrparametrizationsitems)rrrrrrs  rmodmappingcCst||vr]|t|}||}|jD]}||q|jD]}||q#ddt|| D}t |dksFJd|t |dkrRt t |nd}|r[| ||S|S)a%Swaps the module using from_dense according to the mapping passed in. Args: mod: input module mapping: a dictionary that maps from nn module to sparse nn module Return: The corresponding sparse module of `mod` according to mapping, created using from_dense cSsh|]}|jqSr)device)rprrr 6szswap_module..zOswap_module only works with cpu or single-device CUDA modules, but got devices rN)r from_dense_forward_pre_hooksvaluesregister_forward_pre_hook_forward_hooksregister_forward_hookr parametersbufferslennextiterto)rr sparse_modnew_mod pre_hook_fnhook_fndevicesr rrrr s     r modelprefixcCsH||urdS|D]\}}t||d}t|tr!|||Sq dS)zS Returns the fqn for a module or None if module not a descendent of model. r5.N)named_childrenr rstr)r6rr7namechildfqnrrrr Ds  r pathcCs(|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. r5r8N)splitgetattr)r6r>r;rrrr Ssr tensor_fqncCs@|dd}|dt| d|v}t||}||||dS)zX Uses tensor_fqn to obtain a dict containing module_fqn, module and tensor_name r8N) module_fqnr tensor_namerA)r?r,r )r6rArDrCrrrrr ^s r cs0eZdZdZfddZddZddZZS)r a;Parametrization for the weights. Should be attached to the 'weight' or any other parameter 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__register_buffer)selfrE __class__rrrG~s zFakeSparsity.__init__cCs|jj|jks J|j|Sr)rEshape)rIxrrrforwards zFakeSparsity.forwardcOsiSrr)rIargskwargsrrr state_dictszFakeSparsity.state_dict)__name__ __module__ __qualname____doc__rGrNrQ __classcell__rrrJrr ss  r N)r5) itertoolsrtypingrrtorchrtorch.nn.utils.parametrizerr__all__Moduletypeboolrdictr r:r r r r rrrrs4     ( "