deepy/networks/network.py
def register_layer(self, layer):
        """
        Register the layer so that it's param will be trained.
        But the output of the layer will not be stacked.
        """
        if type(layer) == Block:
            layer.fix()
        self.parameter_count += layer.parameter_count
        self.parameters.extend(layer.parameters)
        self.free_parameters.extend(layer.free_parameters)
        self.training_monitors.extend(layer.training_monitors)
        self.testing_monitors.extend(layer.testing_monitors)
        self.updates.extend(layer.updates)
        self.training_updates.extend(layer.training_updates)
        self.input_variables.extend(layer.external_inputs)
        self.target_variables.extend(layer.external_targets)

        self.training_callbacks.extend(layer.training_callbacks)
        self.testing_callbacks.extend(layer.testing_callbacks)
        self.epoch_callbacks.extend(layer.epoch_callbacks)
def register_layer(self, layer):
        """
        Register the layer so that it's param will be trained.
        But the output of the layer will not be stacked.
        """
        if type(layer) == Block:
            layer.fix()
        self.parameter_count += layer.parameter_count
        self.parameters.extend(layer.parameters)
        self.free_parameters.extend(layer.free_parameters)
        self.training_monitors.extend(layer.training_monitors)
        self.testing_monitors.extend(layer.testing_monitors)
        self.updates.extend(layer.updates)
        self.training_updates.extend(layer.training_updates)
        self.input_variables.extend(layer.external_inputs)
        self.target_variables.extend(layer.external_targets)

        self.training_callbacks.extend(layer.training_callbacks)
        self.testing_callbacks.extend(layer.testing_callbacks)
        self.epoch_callbacks.extend(layer.epoch_callbacks)
Register the layer so that it's param will be trained.
        But the output of the layer will not be stacked.