import tensorflow as tf

            alpha_var: variable, alpha for weighted sum of fade-in of layers.
            params: dict, user passed parameters.
            trans_idx: int, index of current growth transition.

        Returns:
            Final logits tensor of discriminator.
        """
        print_obj(
            "\nEntered create_growth_transition_discriminator_network",
            "trans_idx",
            trans_idx
        )
        print_obj("create_growth_transition_discriminator_network", "X", X)
        with tf.variable_scope(name_or_scope=self.name, reuse=tf.AUTO_REUSE):
            # Growing side chain.
            growing_from_rgb_conv_layer = self.from_rgb_conv_layers[trans_idx + 1]
            growing_block_layers = self.conv_layer_blocks[trans_idx + 1]

            # Pass inputs through layer chain.
            growing_block_conv = growing_from_rgb_conv_layer(inputs=X)
            print_obj(
                "\ncreate_growth_transition_discriminator_network",
                "growing_block_conv",
                growing_block_conv
            )
            for i in range(len(growing_block_layers)):
