multiml.task.keras.modules.ensemble module

class multiml.task.keras.modules.ensemble.EnsembleModel(*args, **kwargs)

Bases: Model

__init__(models, prefix, ensemble_type, dropout_rate=None, individual_loss=False, *args, **kwargs)

Constructor.

Parameters:

• models (list(tf.keras.Model)) – list of keras models for ensembling

• prefix (str) – prefix for a layer’s name

• ensemble_type (str) – type of ensemble way (linear or softmax)

• dropout_rate (float) – dropout rate. Valid only for ensemble_type = softmax

• individual_loss (bool) – use multiple outputs

call(inputs, training=False)

Calls the model on new inputs.

In this case call just reapplies all ops in the graph to the new inputs (e.g. build a new computational graph from the provided inputs).

Parameters:

• inputs – A tensor or list of tensors.

• training – Boolean or boolean scalar tensor, indicating whether to run the Network in training mode or inference mode.

• mask – A mask or list of masks. A mask can be either a tensor or None (no mask).

Returns:

A tensor if there is a single output, or a list of tensors if there are more than one outputs.