o پi@sdZddlZddlZddlmZmZmZmZmZddl Z zddl Z dZ Wn e y/dZ YnweeZgdZdeded efd d Zd eeefd eeeffd dZ   d$dededeee jfded eeeff ddZ      d%de jjdededeee jfdededeeded efddZ d&d eeefde jjded eeeffddZ   d'de jjdedee jjd eed!ed eef d"d#ZdS)(zi Model creation / weight loading / state_dict helpers Hacked together by / Copyright 2020 Ross Wightman N)AnyCallableDictOptionalUnionTF)clean_state_dictload_state_dictload_checkpointremap_state_dictresume_checkpointtextprefixreturncCs||r |t|dS|S)N) startswithlen)r r rH/home/ubuntu/.local/lib/python3.10/site-packages/timm/models/_helpers.py_remove_prefixs r state_dictcCs:i}d}|D]\}}|D]}t||}q|||<q|S)N)zmodule.z _orig_mod.)itemsr)rcleaned_state_dict to_removekvrrrrrs  rcpucheckpoint_pathuse_emadevice weights_onlycCs|r|tj|r|t|drtsJdtjj||d}nz tj |||d}Wnt y8tj ||d}Ynwd}t |t rg|rM| dddurMd}n|rZ| d ddurZd }n d |vrad }nd |vrgd }t|rn||n|}td |||Std |t)a_Load state dictionary from checkpoint file. Args: checkpoint_path: Path to checkpoint file. use_ema: Whether to use EMA weights if available. device: Device to load checkpoint to. weights_only: Whether to load only weights (torch.load parameter). Returns: State dictionary loaded from checkpoint. z .safetensorsz-`pip install safetensors` to use .safetensors)r map_locationr)r!state_dict_emaN model_emarmodelzLoaded {} from checkpoint '{}'No checkpoint found at '{}')ospathisfilestrendswith_has_safetensors safetensorstorch load_fileload TypeError isinstancedictgetr_loggerinfoformaterrorFileNotFoundError)rrrr checkpointstate_dict_keyrrrrr,s0   rr%strictremap filter_fnc Csxtj|ddvrt|dr||dStdt||||d}|r,t||}n|r3|||}|j||d} | S)a<Load checkpoint into model. Args: model: Model to load checkpoint into. checkpoint_path: Path to checkpoint file. use_ema: Whether to use EMA weights if available. device: Device to load checkpoint to. strict: Whether to strictly enforce state_dict keys match. remap: Whether to remap state dict keys by order. filter_fn: Optional function to filter state dict. weights_only: Whether to load only weights (torch.load parameter). Returns: Incompatible keys from model.load_state_dict(). )z.npzz.npyload_pretrainedz"Model cannot load numpy checkpointN)rr)r<) r'r(splitextlowerhasattrr@NotImplementedErrorrr ) r%rrrr<r=r>rrincompatible_keysrrrr Zs    r allow_reshapec Csi}t||D]I\\}}\}}||ks0Jd|d|jd|d|jd |j|jkrR|r?||j}nJd|d|jd|d|jd |||<q |S)aRemap checkpoint by iterating over state dicts in order (ignoring original keys). This assumes models (and originating state dict) were created with params registered in same order. Args: state_dict: State dict to remap. model: Model whose state dict keys to use. allow_reshape: Whether to allow reshaping tensors to match. Returns: Remapped state dictionary. zTensor size mismatch z: z vs z. Remap failed.FzTensor shape mismatch )ziprrnumelshapereshape)rr%rFout_dictkavakbvbrrrr s&6 & r optimizer loss_scalerlog_infocCs4d}tj|rtj|ddd}t|tr~d|vr~|r tdt |d}| ||durAd|vrA|r:td| |d|durY|j |vrY|rQtd | ||j d |vr||d }d |vro|d d kro|d 7}|r|td ||d |S| ||rtd ||St d |t)azResume training from checkpoint. Args: model: Model to load checkpoint into. checkpoint_path: Path to checkpoint file. optimizer: Optional optimizer to restore state. loss_scaler: Optional AMP loss scaler to restore state. log_info: Whether to log loading info. Returns: Resume epoch number if available, else None. NrFr rz(Restoring model state from checkpoint...rPz,Restoring optimizer state from checkpoint...z2Restoring AMP loss scaler state from checkpoint...epochversionz!Loaded checkpoint '{}' (epoch {})zLoaded checkpoint '{}'r&)r'r(r)r.r0r2r3r5r6rrr;r7r8r9)r%rrPrQrR resume_epochr:rrrrr s:       r )TrF)TrTFNF)T)NNT) __doc__loggingr'typingrrrrrr.safetensors.torchr-r, ImportError getLogger__name__r5__all__r*rrboolrrnnModuler r optim Optimizerintr rrrrs  "   1  -