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)
