code: def default_hyper_parameters(cls) -> Dict[str, Dict[str, Any]]:
      return {
          "conv_layer1": {
              "filters": 264,
              "kernel_size": 3,
              "padding": "same",
              "activation": "relu",
          },
          "conv_layer2": {
              "filters": 128,
              "kernel_size": 3,
              "padding": "same",
              "activation": "relu",
          },
          "conv_layer3": {
              "filters": 64,
              "kernel_size": 3,
              "padding": "same",
              "activation": "relu",
          },
          "layer_output": {},
      }
  
file_path: Kashgari/kashgari/tasks/classification/cnn_attention_model.py
imports: from abc import ABC
  from typing import Dict, Any
  import tensorflow
  import tensorflow.keras.layers
  from tensorflow import keras
  from kashgari.logger import logger
  from kashgari.tasks.classification.abc_model import ABCClassificationModel
label_desc: Use image node_id 1 for calling the CNN_Attention_Model obj's underlying member method code with example usage: obj.default_hyper_parameters(cls) and returns: dict