[{'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:# model=Sequential()\n# model.add(Conv2D(64,kernel_size=(2,2),strides=(1,1),kernel_initializer=glorot_normal(seed=100),input_shape=(64,64,3) ))\n# model.add(Conv2D(64,kernel_size=(2,2),strides=(1,1),kernel_initializer=glorot_normal(seed=100)))\n# model.add(BatchNormalization())\n# model.add(Activation("relu"))\n# model.add(MaxPooling2D((2,2)))\n\n# model.add(Conv2D(128,kernel_size=(2,2),strides=(1,1),kernel_initializer=glorot_normal(seed=100)))\n# model.add(Conv2D(128,kernel_size=(2,2),strides=(1,1),kernel_initializer=glorot_normal(seed=100)))\n# model.add(BatchNormalization())\n# model.add(Activation("relu"))\n# model.add(MaxPooling2D((2,2)))\n\n# model.add(Conv2D(256,kernel_size=(2,2),strides=(1,1),kernel_initializer=glorot_normal(seed=100)))\n# model.add(Conv2D(256,kernel_size=(2,2),strides=(1,1),kernel_initializer=glorot_normal(seed=100)))\n# model.add(Conv2D(256,kernel_size=(2,2),strides=(1,1),kernel_initializer=glorot_normal(seed=100)))\n# model.add(BatchNormalization())\n# model.add(Activation("relu"))\n# model.add(MaxPooling2D((2,2)))\n\n\n# model.add(Conv2D(512,kernel_size=(2,2),strides=(1,1),kernel_initializer=glorot_normal(seed=100)))\n# model.add(Conv2D(512,kernel_size=(2,2),strides=(1,1),kernel_initializer=glorot_normal(seed=100)))\n# model.add(Conv2D(512,kernel_size=(2,2),strides=(1,1),kernel_initializer=glorot_normal(seed=100)))\n# model.add(BatchNormalization())\n# model.add(Activation("relu"))\n# model.add(MaxPooling2D((2,2)))\n\n\n# model.add(Flatten())\n# model.add(Dense(10,activation="relu",kernel_initializer=glorot_normal(seed=100)))\n# model.add(Dense(1,activation="sigmoid",kernel_initializer=glorot_normal(seed=100)))\n\n\n\n\n\n\n\n'}, {'role': 'assistant', 'content': 'helper_functions'}]