Shorten module paths with new 'nn' dir (#96)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ultralytics/yolo/engine/model.py

@@ -2,14 +2,13 @@ import torch
 import yaml
 
 from ultralytics import yolo  # noqa required for python usage
+from ultralytics.nn.tasks import ClassificationModel, DetectionModel, SegmentationModel, attempt_load_weights
 # from ultralytics.yolo.data.utils import check_dataset, check_dataset_yaml
 from ultralytics.yolo.engine.trainer import DEFAULT_CONFIG
 from ultralytics.yolo.utils import LOGGER
 from ultralytics.yolo.utils.checks import check_yaml
 from ultralytics.yolo.utils.configs import get_config
 from ultralytics.yolo.utils.files import yaml_load
-from ultralytics.yolo.utils.modeling import attempt_load_weights
-from ultralytics.yolo.utils.modeling.tasks import ClassificationModel, DetectionModel, SegmentationModel
 from ultralytics.yolo.utils.torch_utils import smart_inference_mode
 
 # map head: [model, trainer, validator, predictor]

ultralytics/yolo/engine/predictor.py

@@ -30,13 +30,13 @@ from pathlib import Path
 
 import cv2
 
+from ultralytics.nn.autobackend import AutoBackend
 from ultralytics.yolo.data.dataloaders.stream_loaders import LoadImages, LoadScreenshots, LoadStreams
 from ultralytics.yolo.data.utils import IMG_FORMATS, VID_FORMATS, check_dataset, check_dataset_yaml
 from ultralytics.yolo.utils import LOGGER, ROOT, colorstr, ops
 from ultralytics.yolo.utils.checks import check_file, check_imshow
 from ultralytics.yolo.utils.configs import get_config
 from ultralytics.yolo.utils.files import increment_path
-from ultralytics.yolo.utils.modeling.autobackend import AutoBackend
 from ultralytics.yolo.utils.torch_utils import check_imgsz, select_device, smart_inference_mode
 
 DEFAULT_CONFIG = ROOT / "yolo/utils/configs/default.yaml"
@@ -95,7 +95,7 @@ class BasePredictor:
         device = select_device(self.args.device)
         model = model or self.args.model
         self.args.half &= device.type != 'cpu'  # half precision only supported on CUDA
-        model = AutoBackend(model, device=device, dnn=self.args.dnn, fp16=self.args.half)  # NOTE: not passing data
+        model = AutoBackend(model, device=device, dnn=self.args.dnn, fp16=self.args.half)
         stride, pt = model.stride, model.pt
         imgsz = check_imgsz(self.args.imgsz, s=stride)  # check image size
 

ultralytics/yolo/engine/validator.py

@@ -4,11 +4,11 @@ import torch
 from omegaconf import OmegaConf
 from tqdm import tqdm
 
+from ultralytics.nn.autobackend import AutoBackend
 from ultralytics.yolo.data.utils import check_dataset, check_dataset_yaml
 from ultralytics.yolo.engine.trainer import DEFAULT_CONFIG
 from ultralytics.yolo.utils import LOGGER, TQDM_BAR_FORMAT
 from ultralytics.yolo.utils.files import increment_path
-from ultralytics.yolo.utils.modeling.autobackend import AutoBackend
 from ultralytics.yolo.utils.ops import Profile
 from ultralytics.yolo.utils.torch_utils import check_imgsz, de_parallel, select_device, smart_inference_mode