Add a flatten layer. Only flattens the channel, height and width axis. Leaves the sequence axis as is.

        Parameters
        ----------
        name: str
            The name of this layer.
        mode: int

            - If mode == 0, the flatten layer is in CHANNEL_FIRST mode.
            - If mode == 1, the flatten layer is in CHANNEL_LAST mode.

        input_name: str
            The input blob name of this layer.
        output_name: str
            The output blob name of this layer.

        See Also
        --------
        add_permute, add_reshape

def add_flatten(self, name, mode, input_name, output_name):
        """
        Add a flatten layer. Only flattens the channel, height and width axis. Leaves the sequence axis as is.

        Parameters
        ----------
        name: str
            The name of this layer.
        mode: int

            - If mode == 0, the flatten layer is in CHANNEL_FIRST mode.
            - If mode == 1, the flatten layer is in CHANNEL_LAST mode.

        input_name: str
            The input blob name of this layer.
        output_name: str
            The output blob name of this layer.

        See Also
        --------
        add_permute, add_reshape
        """
        spec = self.spec
        nn_spec = self.nn_spec

        # Add a new layer
        spec_layer = nn_spec.layers.add()
        spec_layer.name = name
        spec_layer.input.append(input_name)
        spec_layer.output.append(output_name)
        spec_layer_params = spec_layer.flatten

        # Set the parameters
        if mode == 0:
            spec_layer_params.mode = \
                        _NeuralNetwork_pb2.FlattenLayerParams.FlattenOrder.Value('CHANNEL_FIRST')
        elif mode == 1:
            spec_layer_params.mode = \
                        _NeuralNetwork_pb2.FlattenLayerParams.FlattenOrder.Value('CHANNEL_LAST')
        else:
            raise NotImplementedError(
                'Unknown flatten mode %d ' % mode)