o پiU@s0ddlZddlZddlZddlmZddlmZddlmZm Z m Z m Z m Z m Z mZmZmZddlmZddlmZddlmZmZmZmZddlmZdd lmZdd lmZm Z m!Z!m"Z"m#Z#m$Z$dd l%m&Z&dd l'm(Z(dd l)m*Z*ddl+m,Z,e-e.Z/da0da1e2ej34dddkZ5gdZ6edej7dZ8de e9efde e9e9ffddZ:dAde;ddfddZ  # $   dCdej7de e e9efd%e2d&e2d'e e d(e;d e ee9efddfd)d*Z?de e9efde e9effd+d,Z@d-e e9efd.e e9ddfd/d0ZAdDd1d2ZB  dEd3e9de ee9e e9effd4e e e9efde(fd5d6ZC        dFd7eee8e d8e8ffd3e9d9e;de e d4e e d:e ed;e e de e e9de8fd?d@ZDdS)GN)deepcopy)Path) AnyCallableDictListOptionalTupleTypeTypeVarUnion)nn)load_state_dict_from_url)FeatureListNetFeatureDictNetFeatureHookNetFeatureGetterNet)FeatureGraphNet)load_state_dict) has_hf_hubdownload_cached_filecheck_cached_fileload_state_dict_from_hfload_state_dict_from_pathload_custom_from_hf)adapt_input_conv) PretrainedCfg)adapt_model_from_file)get_pretrained_cfgFTIMM_USE_OLD_CACHE) set_pretrained_download_progressset_pretrained_check_hashload_custom_pretrainedload_pretrainedpretrained_cfg_for_featuresresolve_pretrained_cfgbuild_model_with_cfgModelT)boundpretrained_cfgreturnc Cs |dd}|dd}|dd}|dd}|dd}d}d}|dkr4tdd r4d}|s1J|}n>|d kr=d }|}n5|rKd}|}t|tsJJn'|rRd}|}n d }tr^|r\t|nd }|sl|rltdd rld}|}n|rrd}|}|dkr|d dr||d f}||fS) Nsourceurlfile state_dict hf_hub_idhf-hubT) necessary local-dirFhf_hub_filename)getr isinstancedict_USE_OLD_CACHEr) r) cfg_sourcepretrained_urlpretrained_file pretrained_sdr0 load_frompretrained_locold_cache_validr@H/home/ubuntu/.local/lib/python3.10/site-packages/timm/models/_builder.py_resolve_pretrained_source+sB      rBTenablecC|adS)zA Set download progress for pretrained weights on/off (globally). 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Args: model: The instantiated model to load weights into pretrained_cfg: Default pretrained model cfg load_fn: An external standalone fn that loads weights into provided model, otherwise a fn named 'load_pretrained' on the model will be called if it exists cache_dir: Override model checkpoint cache dir for this load r)Nz/Invalid pretrained config, cannot load weights.zHNo pretrained weights exist for this model. 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Will adapt pretrained if different. in_chans: Number of input chans for target model. Will adapt pretrained if different. filter_fn: state_dict filter fn for load (takes state_dict, model as args) strict: Strict load of checkpoint cache_dir: Override model checkpoint cache dir for this load r)NzWInvalid pretrained config, cannot load weights. Use `pretrained=False` for random init.r/z*Loading pretrained weights from state dictr.z&Loading pretrained weights from file () custom_loadFr-z%Loading pretrained weights from url ()rMrLrKcpuT) map_locationrMrL weights_only model_dir)r[rMrLr]r1z2Loading pretrained weights from Hugging Face hub (hfrK)r\rKr3z1Loading pretrained weights from local directory (z#Specified path is not a directory: architecturez this modelz No pretrained weights exist for z). 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This may be expected if model is being adapted.)rN RuntimeErrorrBrOinfor5r#rrrErHr TypeErrorr6listtuplestrrrris_dirrrNotImplementedErrorrPpop missing_keysjoinunexpected_keys)rIr)rTrUrVrWrKr=r>r/rYpretrained_path model_namee input_convsinput_conv_name weight_name classifiersrbclassifier_nameclassifier_weightclassifier_bias load_resultr@r@rAr#s                        r#cCs&t|}d}|D]}||dq|S)N)rTra global_pool)rrk)r) to_removetrr@r@rAr$#s r$kwargsnamescCs&|r|sdS|D]}||dqdS)N)rk)r}r~nr@r@rA_filter_kwargs,s rcCs d}|ddr |d7}|D]o}|dkr1|dd}|dur0t|dks&J|||d dq|d krP|dd}|durOt|dksGJ|||d q|d krk||d}|durj|d krj||||q||d}|dur}||||qt||d dS)a& Update the default_cfg and kwargs before passing to model Args: pretrained_cfg: input pretrained cfg (updated in-place) kwargs: keyword args passed to model build fn (updated in-place) kwargs_filter: keyword arg keys that must be removed before model __init__ )rTrzrUfixed_input_sizeF)img_sizer input_sizeNrSrUrrT)r~)r5len setdefaultr)r)r} kwargs_filterdefault_kwarg_namesrr default_valr@r@rA_update_default_model_kwargs3s4     rvariantpretrained_cfg_overlaycCs|}d}|rt|trtdi|}n t|tr|}d}|s+|r'd||g}t|}|s9td|dt}|ps  ,           "0 3 " " + (