[{'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:def make_layer_vis(model, layer_i):\noutput_getter = K.function([model.layers[0].input, K.learning_phase()],\n[model.layers[layer_i].output])\ndef _impl(img):\ninp = numpy.expand_dims(numpy.expand_dims(numpy.array(img), -1), 0)\noutp = output_getter([inp, False])[0]\nflat = numpy.rollaxis(outp, -1, 2).reshape((outp.shape[1], outp.shape[2]*outp.shape[-1]))\nreturn Image.fromarray((flat*255).astype('uint8'), mode='L')\nreturn _impl\ndef vis_layer(img, model):\nvisualizers = [(model.layers[i], make_layer_vis(model, i))\nfor i in (i for i in range(len(model.layers))\nif not isinstance(model.layers[i],\n(Dropout,\nBatchNormalization,\nActivation)))]\nfor layer, v in visualizers:\ndisplay(layer.name)\ndisplay(v(img))\ntime.sleep(1.0)\nvis_img = val_in[1, :, :, 0]\nvis_layer(vis_img, model)"}, {'role': 'assistant', 'content': "['result_visualization']"}]