g^(h ddlmZddlmZmZddlmZddlmZm Z gdZ dejde ejde fd Zd ejd ee eje ejfdejfd Z dd ejdejdedeefdZd eejdedeejfdZd ejdedeeeffdZGddejZy))chain)AnyOptional)nn)is_parametrizedtype_before_parametrizations)module_contains_param swap_module module_to_fqn fqn_to_moduleget_arg_info_from_tensor_fqn FakeSparsitymoduleparametrizationreturnctt|r,tfd|jjDSy)Nc3LK|]\}}tfd|Dyw)c36K|]}t|ywN) isinstance).0paramrs _/var/www/skyplay_api_hub/venv/lib/python3.12/site-packages/torch/ao/pruning/sparsifier/utils.py z2module_contains_param...sKu 5/2KsN)any)rkey param_listrs rrz(module_contains_param..s( Z K K K s!$F)rrparametrizationsitems)rrs `rr r s9v #)#:#:#@#@#B    modmappingcJt||vr|t|}|j|}|jjD]}|j ||j jD]}|j |t|j|jDchc]}|j}}t|dks Jd|t|dkDrtt|nd}|r|j||S|Scc}w)a%Swaps the module using from_dense according to the mapping passed in. Args: mod: input module mapping: a dictionary that maps from nn module to sparse nn module Return: The corresponding sparse module of `mod` according to mapping, created using from_dense zOswap_module only works with cpu or single-device CUDA modules, but got devices rN)r from_dense_forward_pre_hooksvaluesregister_forward_pre_hook_forward_hooksregister_forward_hookr parametersbuffersdevicelennextiterto) r!r" sparse_modnew_mod pre_hook_fnhook_fnpdevicesr-s rr r s$C(G39#>? '',1188: ;K  - -k : ;))002 3G  ) )' 2 3&+3>>+;S[[]%KL188LL LA  g \]d\e f g (+G q(8d7m$d  JJv  Ms8D modelprefixc||ury|jD],\}}t||d}t|ts$||z|zcSy)zS Returns the fqn for a module or None if module not a descendent of model. .N)named_childrenr rstr)r8rr9namechildfqns rr r DsV ++-' eE63/ c3 D=3& &' r pathcV|dk7r#|jdD]}t||d}|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;r<N)splitgetattr)r8rBr?s rr r Ss5  rzJJsO /DE4.E / Lr tensor_fqncx|jdd}|dt| d|vz }t||}||||dS)zX Uses tensor_fqn to obtain a dict containing module_fqn, module and tensor_name r<N) module_fqnr tensor_namerF)rDr.r )r8rFrJrIrs rr r ^s\""3'+KEs;//3*3DEFJ 5* -F!"  r c.eZdZdZfdZdZdZxZS)ra;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. cFt||jd|y)Nmask)super__init__register_buffer)selfrM __class__s rrOzFakeSparsity.__init__~s  VT*r cj|jj|jk(sJ|j|zSr)rMshape)rQxs rforwardzFakeSparsity.forwards*yy!'')))yy1}r ciSr)rQargskwargss r state_dictzFakeSparsity.state_dicts  r )__name__ __module__ __qualname____doc__rOrVr[ __classcell__)rRs@rrrss+r rN)r;) itertoolsrtypingrrtorchrtorch.nn.utils.parametrizerr__all__Moduletypeboolr dictr r>r r r rrXr rrjs T "))d299oRV$ $!$ryy/4 ?"BC$YY$P8:  99  ii 14  c] ")),CHRYY