dcase_models.model.ModelContainer¶

class dcase_models.model.ModelContainer(model=None, model_path=None, model_name='ModelContainer', metrics=['classification'])[source]¶

Bases: object

Abstract base class to store and manage models.

Parameters:	model : keras model or similar Object that defines the model (i.e keras.models.Model) model_path : str Path to the model file model_name : str Model name metrics : list of str List of metrics used for evaluation

__init__(model=None, model_path=None, model_name='ModelContainer', metrics=['classification'])[source]¶

Initialize ModelContainer

Parameters:	model : keras model or similar Object that defines the model (i.e keras.models.Model) model_path : str Path to the model file model_name : str Model name metrics : list of str List of metrics used for evaluation

Methods

`__init__`([model, model_path, model_name, …])	Initialize ModelContainer
`build`()	Missing docstring here
`check_if_model_exists`(folder, **kwargs)	Missing docstring here
`evaluate`(X_test, Y_test[, scaler])	Missing docstring here
`get_available_intermediate_outputs`()	Missing docstring here
`get_intermediate_output`(output_ix_name)	Missing docstring here
`get_number_of_parameters`()	Missing docstring here
`load_model_from_json`(folder, **kwargs)	Missing docstring here
`load_model_weights`(weights_folder)	Missing docstring here
`save_model_json`(folder)	Missing docstring here
`save_model_weights`(weights_folder)	Missing docstring here
`train`()	Missing docstring here

evaluate(X_test, Y_test, scaler=None)[source]¶: Missing docstring here

get_intermediate_output(output_ix_name)[source]¶: Missing docstring here