[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:"""\nDON\'T MODIFY ANYTHING IN THIS CELL\n"""\nimport numpy as np\ndef show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):\n"""\nShow example output for the generator\n:param sess: TensorFlow session\n:param n_images: Number of Images to display\n:param input_z: Input Z Tensor\n:param out_channel_dim: The number of channels in the output image\n:param image_mode: The mode to use for images ("RGB" or "L")\n"""\ncmap = None if image_mode == \'RGB\' else \'gray\'\nz_dim = input_z.get_shape().as_list()[-1]\nexample_z = np.random.uniform(-1, 1, size=[n_images, z_dim])\nsamples = sess.run(\ngenerator(input_z, out_channel_dim, False),\nfeed_dict={input_z: example_z})\nimages_grid = helper.images_square_grid(samples, image_mode)\npyplot.imshow(images_grid, cmap=cmap)\npyplot.show()'}, {'role': 'assistant', 'content': "['helper_functions', 'result_visualization']"}]