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This decorator ensures that only the keyword arguments that match the function's signature, or are specified in the `extra` list, are passed to the function. Any additional keyword arguments are filtered out and a warning is issued. Parameters: extra (`Optional[list]`, *optional*): A list of extra keyword argument names that are allowed even if they are not in the function's signature. Returns: Callable: A decorator that wraps the function and filters out invalid keyword arguments. Example usage: ```python @filter_out_non_signature_kwargs(extra=["allowed_extra_arg"]) def my_function(arg1, arg2, **kwargs): print(arg1, arg2, kwargs) my_function(arg1=1, arg2=2, allowed_extra_arg=3, invalid_arg=4) # This will print: 1 2 {"allowed_extra_arg": 3} # And issue a warning: "The following named arguments are not valid for `my_function` and were ignored: 'invalid_arg'" ``` ctj}t|jj }|j d|vd|vd_tfd}|S)NrrTci}i}|jD]\}}| vr|||<|||<|r|Dcgc]}d|d }}dj|} r|djjdz}n r|djdz}nd}t j d|jd|t d |i|Scc}w) N'z, rrr?z1The following named arguments are not valid for `z` and were ignored: r) stacklevel)rjoinrrwarningswarn UserWarning) rr valid_kwargsinvalid_kwargsrrinvalid_kwargs_names cls_prefixfuncis_class_methodis_instance_methodvalid_kwargs_to_passs r/wrapperzCfilter_out_non_signature_kwargs..decorator..wrapper sLN  *1,,&'LO()N1%  * :H'IQ!A3a'I$'I'+yy1E'F$&!%a!2!2!;!;c!AJ$!%a!1!1C!7J!#J G |TXTaTaSbc**>)?A .. .%(Js B?)r'r(setr,runion _filter_out_non_signature_kwargsr)r~sigfunction_named_argsrrrrextra_params_to_passs` @@@r/ decoratorz2filter_out_non_signature_kwargs..decorators}%!#.."5"5"782889MN$'::#6615- t /  />r1)r)rprrs @r/filter_out_non_signature_kwargsrs&6 KREu:,\ r1ceZdZUdZeded<eeed<eeed<eeed<eded<eded <eeed <eeed <y ) TransformersKwargsat Keyword arguments to be passed to the forward pass of a `PreTrainedModel`. 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It is recommended to pass it when you are doing gradient accumulation. output_hidden_states (`Optional[bool]`, *optional*): Most of the models support outputting all hidden states computed during the forward pass. output_attentions (`Optional[bool]`, *optional*): Turn this on to return the intermediary attention scores. output_router_logits (`Optional[bool]`, *optional*): For MoE models, this allows returning the router logits to compute the loss. cu_seq_lens_q (`torch.LongTensor`, *optional*) Gets cumulative sequence length for query state. cu_seq_lens_k (`torch.LongTensor`, *optional*) Gets cumulative sequence length for key state. max_length_q (`int`, *optional*): Maximum sequence length for query state. max_length_k (`int`, *optional*): Maximum sequence length for key state. z torch.Tensornum_items_in_batchoutput_hidden_statesoutput_attentionsoutput_router_logitsztorch.LongTensor cu_seq_lens_q cu_seq_lens_k max_length_q max_length_kN)rrrrr__annotations__boolrrr1r/rr0s^,!00"4.(~%"4.(.//.//3-3-r1r)total config_dictc d|vS)z3Checks whether a config dict is a timm config dict.pretrained_cfgr)rs r/is_timm_config_dictrQs { **r1pretrained_model_pathc|yt|}tjj|}tjj |}|rE|j dr4t |5}tj|}dddt|S|rtjjtjj|drRt tjj|d5}tj|}dddt|Sy#1swYtSxYw#1swYtSxYw)zA Checks whether a checkpoint is a timm model checkpoint. NFz.jsonz config.json) r8ospathisfileisdirendswithopenjsonloadrexistsrv)ris_fileis_dirr'rs r/is_timm_local_checkpointrVs$ 56ggnn23G WW]]0 1F(11': ' ( 'A))A,K '";//"''...C]!ST "'',,4mD E '))A,K '";//  '";// '";//s+D&<D<&D9<Erfztorch.nn.Modulerrcbt||||jD]}t|||y)z5 Set a value to a module and all submodules. N)rchildrenset_attribute_for_modules)rfrr submodules r/rrrs2 FC__&9 !)S%89r1cvt||r t|||jD]}t||y)z: Delete a value from a module and all submodules. N)rfdelattrrdel_attribute_from_modules)rfrrs r/rr{s8 vs__&3 "9c23r1c.tfd}|S)z Decorator to wrap model method, to call output.to_tuple() if return_dict=False passed as a kwarg or use_return_dict=False is set in the config. 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