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ultralytics 8.1.25 fix **kwargs: (dict) warnings (#8815)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2024-03-09 18:51:38 +01:00 • committed by GitHub
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12 changed files with 22 additions and 22 deletions
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ultralytics/engine/model.py
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@ -161,7 +161,7 @@ class Model(nn.Module):
Defaults to None.
stream (bool, optional): If True, treats the input source as a continuous stream for predictions.
Defaults to False.
**kwargs (dict): Additional keyword arguments for configuring the prediction process.
**kwargs (any): Additional keyword arguments for configuring the prediction process.
Returns:
(List[ultralytics.engine.results.Results]): A list of prediction results, encapsulated in the Results class.
@ -368,7 +368,7 @@ class Model(nn.Module):
source (str | int | PIL.Image | np.ndarray): The source of the image for generating embeddings.
The source can be a file path, URL, PIL image, numpy array, etc. Defaults to None.
stream (bool): If True, predictions are streamed. Defaults to False.
**kwargs (dict): Additional keyword arguments for configuring the embedding process.
**kwargs (any): Additional keyword arguments for configuring the embedding process.
Returns:
(List[torch.Tensor]): A list containing the image embeddings.
@ -406,7 +406,7 @@ class Model(nn.Module):
stream (bool, optional): Treats the input source as a continuous stream for predictions. Defaults to False.
predictor (BasePredictor, optional): An instance of a custom predictor class for making predictions.
If None, the method uses a default predictor. Defaults to None.
**kwargs (dict): Additional keyword arguments for configuring the prediction process. These arguments allow
**kwargs (any): Additional keyword arguments for configuring the prediction process. These arguments allow
for further customization of the prediction behavior.
Returns:
@ -460,7 +460,7 @@ class Model(nn.Module):
source (str, optional): The input source for object tracking. It can be a file path, URL, or video stream.
stream (bool, optional): Treats the input source as a continuous video stream. Defaults to False.
persist (bool, optional): Persists the trackers between different calls to this method. Defaults to False.
**kwargs (dict): Additional keyword arguments for configuring the tracking process. These arguments allow
**kwargs (any): Additional keyword arguments for configuring the tracking process. These arguments allow
for further customization of the tracking behavior.
Returns:
@ -497,7 +497,7 @@ class Model(nn.Module):
Args:
validator (BaseValidator, optional): An instance of a custom validator class for validating the model. If
None, the method uses a default validator. Defaults to None.
**kwargs (dict): Arbitrary keyword arguments representing the validation configuration. These arguments are
**kwargs (any): Arbitrary keyword arguments representing the validation configuration. These arguments are
used to customize various aspects of the validation process.
Returns:
@ -531,7 +531,7 @@ class Model(nn.Module):
configurable options, users should refer to the 'configuration' section in the documentation.
Args:
**kwargs (dict): Arbitrary keyword arguments to customize the benchmarking process. These are combined with
**kwargs (any): Arbitrary keyword arguments to customize the benchmarking process. These are combined with
default configurations, model-specific arguments, and method defaults.
Returns:
@ -570,7 +570,7 @@ class Model(nn.Module):
possible arguments, refer to the 'configuration' section in the documentation.
Args:
**kwargs (dict): Arbitrary keyword arguments to customize the export process. These are combined with the
**kwargs (any): Arbitrary keyword arguments to customize the export process. These are combined with the
model's overrides and method defaults.
Returns:
@ -607,7 +607,7 @@ class Model(nn.Module):
Args:
trainer (BaseTrainer, optional): An instance of a custom trainer class for training the model. If None, the
method uses a default trainer. Defaults to None.
**kwargs (dict): Arbitrary keyword arguments representing the training configuration. These arguments are
**kwargs (any): Arbitrary keyword arguments representing the training configuration. These arguments are
used to customize various aspects of the training process.
Returns:
@ -679,7 +679,7 @@ class Model(nn.Module):
use_ray (bool): If True, uses Ray Tune for hyperparameter tuning. Defaults to False.
iterations (int): The number of tuning iterations to perform. Defaults to 10.
*args (list): Variable length argument list for additional arguments.
**kwargs (dict): Arbitrary keyword arguments. These are combined with the model's overrides and defaults.
**kwargs (any): Arbitrary keyword arguments. These are combined with the model's overrides and defaults.
Returns:
(dict): A dictionary containing the results of the hyperparameter search.