def default_model_fn(model_dir): """Load a model. For XGBoost Framework, a default function to load a model is not provided. Users should provide customized model_fn() in script. Args: model_dir: a directory where model is saved. Returns: A XGBoost model. """ return transformer.default_model_fn(model_dir)
def default_model_fn(model_dir): """Loads a model. For Scikit-learn, a default function to load a model is not provided. Users should provide customized model_fn() in script. Args: model_dir: a directory where model is saved. Returns: A Scikit-learn model. """ return transformer.default_model_fn(model_dir)
def default_model_fn(model_dir): """Loads a model. For PyTorch, a default function to load a model cannot be provided. Users should provide customized model_fn() in script. Args: model_dir: a directory where model is saved. Returns: A PyTorch model. """ return transformer.default_model_fn(model_dir)
def default_model_fn(model_dir): """Function responsible to load the model. For more information about model loading https://github.com/aws/sagemaker-python-sdk#model-loading. Args: model_dir (str): The directory where model files are stored. Returns: (obj) the loaded model. """ return transformer.default_model_fn(model_dir)
def default_model_fn(model_dir): return transformer.default_model_fn(model_dir)