def create(self, architecture: Architecture, metadata: Metadata,
arguments: Configuration) -> Any:
# collect the parameters from the indicated models
parameters = []
for module_name in arguments.parameters:
parameters.extend(architecture[module_name].parameters())
# copy the rest of the arguments
arguments = {}
for key, value in arguments.items():
if key != "parameters":
arguments[key] = value
# create the optimizer
return self.optimizer_class(parameters, **arguments)
def create(self, architecture: Architecture, metadata: Metadata,
arguments: Configuration) -> Any:
# separate arguments
noise_layer_arguments = None
autoencoder_arguments = Configuration()
for argument_name, argument_value in arguments.items():
if argument_name == "noise_layer":
noise_layer_arguments = argument_value
else:
autoencoder_arguments[argument_name] = argument_value
noise_layer = self.create_other(
noise_layer_arguments.factory, architecture, metadata,
noise_layer_arguments.get("arguments", {}))
autoencoder = self.create_other(self.factory_name, architecture,
metadata, autoencoder_arguments)
return DeNoisingAutoencoder(noise_layer, autoencoder)