[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': 'Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:import problem_unittests as tests\ndef model_inputs(image_width, image_height, image_channels, z_dim):\n"""\nCreate the model inputs\n:param image_width: The input image width\n:param image_height: The input image height\n:param image_channels: The number of image channels\n:param z_dim: The dimension of Z\n:return: Tuple of (tensor of real input images, tensor of z data, learning rate)\n"""\nreal_input = tf.placeholder(tf.float32, shape=[None, image_width, image_height, image_channels], name=\'real_input\')\nz = tf.placeholder(tf.float32, shape=[None, z_dim], name=\'z\')\nlearning_rate = tf.placeholder(tf.float32, shape=[], name=\'learning_rate\')\nreturn real_input, z, learning_rate\n"""\nDON\'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE\n"""\ntests.test_model_inputs(model_inputs)'}, {'role': 'assistant', 'content': 'modelling'}]