FPh0 fdZddlmZddlZddlmZddlmZmZddl m Z ddl m Z Gd d eZ y) z YOLO-NAS model interface. Example: ```python from ultralytics import NAS model = NAS('yolo_nas_s') results = model.predict('ultralytics/assets/bus.jpg') ``` )PathN)Model) model_infosmart_inference_mode) NASPredictor) NASValidatorcbeZdZdZdd fd ZededefdZd dZe dZ xZ S) NASa 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. Example: ```python from ultralytics import NAS model = NAS('yolo_nas_s') results = model.predict('ultralytics/assets/bus.jpg') ``` Attributes: model (str): Path to the pre-trained model or model name. Defaults to 'yolo_nas_s.pt'. Note: YOLO-NAS models only support pre-trained models. Do not provide YAML configuration files. cdt|jdvsJdt| |dy)zMInitializes the NAS model with the provided or default 'yolo_nas_s.pt' model.)z.yamlz.ymlz0YOLO-NAS models only support pre-trained models.detect)taskN)rsuffixsuper__init__)selfmodel __class__s gC:\Users\daisl\Desktop\realtime-object-detection\venv\Lib\site-packages\ultralytics/models/nas/model.pyrz NAS.__init__/s4E{!!)::nzNAS._load..>s tzzr cy)NFr!rrrzNAS._load..Aserr )T)super_gradientsrrtorchloadrtrainingmodelsgetfusetensorstridedict enumerate _class_namesnamesis_fusedyamlpt_pathr)rrrr"rs` r_loadz NAS._load4s g%% U?G,DJ r\(1188<rHs,  *J!:R%:Rr