o V h@stdZddlmZddlZddlmZddlmZddlm Z ddl m Z dd l m Z dd lmZGd d d eZdS) z YOLO-NAS model interface. Examples: >>> from ultralytics import NAS >>> model = NAS("yolo_nas_s") >>> results = model.predict("ultralytics/assets/bus.jpg") )PathN)Model)DEFAULT_CFG_DICT)attempt_download_asset) model_info) NASPredictor) NASValidatorcs`eZdZdZddeddffdd Zddeddfd d Zdd edefddZe ddZ Z S)NASaW YOLO NAS model for object detection. This class provides an interface for the YOLO-NAS models and extends the `Model` class from Ultralytics engine. It is designed to facilitate the task of object detection using pre-trained or custom-trained YOLO-NAS models. Attributes: model (torch.nn.Module): The loaded YOLO-NAS model. task (str): The task type for the model, defaults to 'detect'. predictor (NASPredictor): The predictor instance for making predictions. validator (NASValidator): The validator instance for model validation. Examples: >>> from ultralytics import NAS >>> model = NAS("yolo_nas_s") >>> results = model.predict("ultralytics/assets/bus.jpg") Notes: YOLO-NAS models only support pre-trained models. Do not provide YAML configuration files. yolo_nas_s.ptmodelreturnNcs*t|jdvs Jdtj|dddS)z.yml.yamlz0YOLO-NAS models only support pre-trained models.detect)taskN)rsuffixsuper__init__)selfr  __class__P/var/www/vscode/kcb/lib/python3.10/site-packages/ultralytics/models/nas/model.pyr.sz NAS.__init__weightscsddl}t|j}|dkrtt|_n|dkr$|jjj |dd_fdd}jj j_ |j_ dfd d j_ t d gj_ttjjj_d d j_ij_|j_dj_itjj_jdS)z Load an existing NAS model weights or create a new NAS model with pretrained weights. Args: weights (str): Path to the model weights file or model name. task (str, optional): Task type for the model. rNz.ptcoco)pretrained_weightscs j|S)z%Ignore additional __call__ arguments.)r _original_forward)xargskwargsrrr new_forwardDs zNAS._load..new_forwardTcsjSN)r )verboser"rrLszNAS._load.. cSsdS)NFrrrrrr&Osr)T)super_gradientsrrtorchloadrr trainingmodelsgetforwardrfusetensorstridedict enumerate _class_namesnamesis_fusedyamlpt_pathrr overridesr eval)rrrr(rr#rr"r_load3s$    z NAS._loadFTdetailedr%cCst|j||ddS)z Log model information. Args: detailed (bool): Show detailed information about model. verbose (bool): Controls verbosity. Returns: (dict): Model information dictionary. i)r<r%imgsz)rr )rr<r%rrrinfoVs zNAS.infocCsdttdiS)zPReturn a dictionary mapping tasks to respective predictor and validator classes.r) predictor validator)rr r"rrrtask_mapcsz NAS.task_map)r r$)FT) __name__ __module__ __qualname____doc__strrr;boolr>propertyrA __classcell__rrrrr s# r )rEpathlibrr)ultralytics.engine.modelrultralytics.utilsrultralytics.utils.downloadsrultralytics.utils.torch_utilsrpredictrvalr r rrrrs