diff --git a/docs/reference/yolo/utils/tuner.md b/docs/reference/yolo/utils/tuner.md new file mode 100644 index 0000000..bf93000 --- /dev/null +++ b/docs/reference/yolo/utils/tuner.md @@ -0,0 +1,9 @@ +--- +description: Optimize YOLO models' hyperparameters with Ultralytics YOLO's `run_ray_tune` function using Ray Tune and ASHA scheduler. +keywords: Ultralytics YOLO, Hyperparameter Tuning, Ray Tune, ASHAScheduler, Optimization, Object Detection +--- + +## run_ray_tune +--- +### ::: ultralytics.yolo.utils.tuner.run_ray_tune +

diff --git a/mkdocs.yml b/mkdocs.yml index 163a165..3295fb9 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -351,6 +351,7 @@ nav: - plotting: reference/yolo/utils/plotting.md - tal: reference/yolo/utils/tal.md - torch_utils: reference/yolo/utils/torch_utils.md + - tuner: reference/yolo/utils/tuner.md - v8: - classify: - predict: reference/yolo/v8/classify/predict.md diff --git a/setup.py b/setup.py index 59510c3..76f6b7d 100644 --- a/setup.py +++ b/setup.py @@ -46,7 +46,7 @@ setup( 'mkdocs-material', 'mkdocstrings[python]', 'mkdocs-redirects', # for 301 redirects - 'mkdocs-ultralytics-plugin', # for meta descriptions and images, dates and authors + 'mkdocs-ultralytics-plugin>=0.0.21', # for meta descriptions and images, dates and authors ], 'export': ['coremltools>=6.0', 'openvino-dev>=2022.3', 'tensorflowjs'], # automatically installs tensorflow }, diff --git a/ultralytics/yolo/engine/model.py b/ultralytics/yolo/engine/model.py index 2019566..a010f0e 100644 --- a/ultralytics/yolo/engine/model.py +++ b/ultralytics/yolo/engine/model.py @@ -389,15 +389,7 @@ class YOLO: def tune(self, *args, **kwargs): """ - Runs hyperparameter tuning using Ray Tune. - - Args: - data (str): The dataset to run the tuner on. - space (dict, optional): The hyperparameter search space. Defaults to None. - grace_period (int, optional): The grace period in epochs of the ASHA scheduler. Defaults to 10. - gpu_per_trial (int, optional): The number of GPUs to allocate per trial. Defaults to None. - max_samples (int, optional): The maximum number of trials to run. Defaults to 10. - train_args (dict, optional): Additional arguments to pass to the `train()` method. Defaults to {}. + Runs hyperparameter tuning using Ray Tune. See ultralytics.yolo.utils.tuner.run_ray_tune for Args. Returns: (dict): A dictionary containing the results of the hyperparameter search.