[{'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:batch_size = 100\nn_epochs = 5\nexamples = ds.X[:100]\nimgs = [] # reconstructed images\nfig, ax = plt.subplots(1,1)\nfor epoch_i in range(n_epochs):\nfor batch_x, _ in ds.train.next_batch():\nsess.run(optimizer, feed_dict={X: batch_x - mean_img})\nrecon = sess.run(Y, feed_dict={X:examples-mean_img})\nrecon = np.clip((recon+mean_img).reshape((-1,28,28)),0,255)\nimg_i = montage(recon).astype(np.uint8)\nimgs.append(img_i)\nax.imshow(img_i, cmap='gray')\nfig.canvas.draw()\nprint(epoch_i,sess.run(cost, feed_dict={X:batch_x-mean_img}))\ngif.build_gif(imgs, saveto='ae2.gif', cmap='gray')"}, {'role': 'assistant', 'content': "['evaluation', 'modelling']"}]