[{'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:outputs = [loss]\noutputs += grads\nf_outputs = backend.function([combination_image], outputs)\ndef eval_loss_and_grads(x):\nx = x.reshape((1, height, width, 3))\nouts = f_outputs([x])\nloss_value = outs[0]\ngrad_values = outs[1].flatten().astype('float64')\nreturn loss_value, grad_values\nclass Evaluator(object):\ndef __init__(self):\nself.loss_value = None\nself.grads_values = None\ndef loss(self, x):\nassert self.loss_value is None\nloss_value, grad_values = eval_loss_and_grads(x)\nself.loss_value = loss_value\nself.grad_values = grad_values\nreturn self.loss_value\ndef grads(self, x):\nassert self.loss_value is not None\ngrad_values = np.copy(self.grad_values)\nself.loss_value = None\nself.grad_values = None\nreturn grad_values\nevaluator = Evaluator()"}, {'role': 'assistant', 'content': 'modelling'}]