ultralytics 8.0.136 refactor and simplify package (#3748)

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

docs/usage/callbacks.md

@@ -40,7 +40,7 @@ for (result, frame) in model.track/predict():
 
 ## All callbacks
 
-Here are all supported callbacks. See callbacks [source code](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/yolo/utils/callbacks/base.py) for additional details.
+Here are all supported callbacks. See callbacks [source code](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/callbacks/base.py) for additional details.
 
 ### Trainer Callbacks
 

docs/usage/cfg.md

@@ -38,7 +38,7 @@ Where:
 - `MODE` (required) is one of `[train, val, predict, export, track, benchmark]`
 - `ARGS` (optional) are any number of custom `arg=value` pairs like `imgsz=320` that override defaults.
   For a full list of available `ARGS` see the [Configuration](cfg.md) page and `defaults.yaml`
-  GitHub [source](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/yolo/cfg/default.yaml).
+  GitHub [source](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/default.yaml).
 
 #### Tasks
 

docs/usage/cli.md

@@ -70,7 +70,7 @@ Where:
 - `MODE` (required) is one of `[train, val, predict, export, track]`
 - `ARGS` (optional) are any number of custom `arg=value` pairs like `imgsz=320` that override defaults.
   For a full list of available `ARGS` see the [Configuration](cfg.md) page and `defaults.yaml`
-  GitHub [source](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/yolo/cfg/default.yaml).
+  GitHub [source](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/default.yaml).
 
 !!! warning "Warning"
 

docs/usage/engine.md

@@ -15,14 +15,14 @@ custom model and dataloader by just overriding these functions:
 
 * `get_model(cfg, weights)` - The function that builds the model to be trained
 * `get_dataloder()` - The function that builds the dataloader
-  More details and source code can be found in [`BaseTrainer` Reference](../reference/yolo/engine/trainer.md)
+  More details and source code can be found in [`BaseTrainer` Reference](../reference/engine/trainer.md)
 
 ## DetectionTrainer
 
 Here's how you can use the YOLOv8 `DetectionTrainer` and customize it.
 
 ```python
-from ultralytics.yolo.v8.detect import DetectionTrainer
+from ultralytics.models.yolo.detect import DetectionTrainer
 
 trainer = DetectionTrainer(overrides={...})
 trainer.train()
@@ -35,7 +35,7 @@ Let's customize the trainer **to train a custom detection model** that is not su
 simply overloading the existing the `get_model` functionality:
 
 ```python
-from ultralytics.yolo.v8.detect import DetectionTrainer
+from ultralytics.models.yolo.detect import DetectionTrainer
 
 
 class CustomTrainer(DetectionTrainer):
@@ -54,7 +54,7 @@ You now realize that you need to customize the trainer further to:
   Here's how you can do it:
 
 ```python
-from ultralytics.yolo.v8.detect import DetectionTrainer
+from ultralytics.models.yolo.detect import DetectionTrainer
 from ultralytics.nn.tasks import DetectionModel
 
 

docs/usage/python.md

@@ -240,7 +240,7 @@ their specific use case based on their requirements for speed and accuracy.
     
         Benchmark an official YOLOv8n model across all export formats.
         ```python
-        from ultralytics.yolo.utils.benchmarks import benchmark
+        from ultralytics.utils.benchmarks import benchmark
         
         # Benchmark
         benchmark(model='yolov8n.pt', imgsz=640, half=False, device=0)
@@ -256,7 +256,7 @@ from `BaseTrainer`.
 !!! tip "Detection Trainer Example"
 
         ```python
-        from ultralytics.yolo import v8 import DetectionTrainer, DetectionValidator, DetectionPredictor
+        from ultralytics.models.yolo import DetectionTrainer, DetectionValidator, DetectionPredictor
 
         # trainer
         trainer = DetectionTrainer(overrides={})