docstr: The default hyper parameters of the model dict, **all models must implement this function.**
  
  You could easily change model's hyper-parameters.
  
  For example, change the LSTM unit in BiLSTM_Model from 128 to 32.
  
      >>> from kashgari.tasks.classification import BiLSTM_Model
      >>> hyper = BiLSTM_Model.default_hyper_parameters()
      >>> print(hyper)
      {'layer_bi_lstm': {'units': 128, 'return_sequences': False}, 'layer_output': {}}
      >>> hyper['layer_bi_lstm']['units'] = 32
      >>> model = BiLSTM_Model(hyper_parameters=hyper)
  
  Returns:
      hyper params dict
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code: def default_hyper_parameters(cls) -> Dict[str, Dict[str, Any]]:
      """
      The default hyper parameters of the model dict, **all models must implement this function.**
  
      You could easily change model's hyper-parameters.
  
      For example, change the LSTM unit in BiLSTM_Model from 128 to 32.
  
          >>> from kashgari.tasks.classification import BiLSTM_Model
          >>> hyper = BiLSTM_Model.default_hyper_parameters()
          >>> print(hyper)
          {'layer_bi_lstm': {'units': 128, 'return_sequences': False}, 'layer_output': {}}
          >>> hyper['layer_bi_lstm']['units'] = 32
          >>> model = BiLSTM_Model(hyper_parameters=hyper)
  
      Returns:
          hyper params dict
      """
      raise NotImplementedError
  
file_path: Kashgari/kashgari/tasks/abs_task_model.py
imports: import json
  import os
  import pathlib
  from abc import ABC, abstractmethod
  from typing import TYPE_CHECKING, Any, Dict, Union
  import tensorflow
  import kashgari
  from kashgari.embeddings import ABCEmbedding
  from kashgari.layers import KConditionalRandomField
  from kashgari.logger import logger
  from kashgari.processors.abc_processor import ABCProcessor
  from kashgari.utils import load_data_object
label_desc: Use image node_id 3 for calling the ABCTaskModel obj's underlying member method code with example usage: obj.default_hyper_parameters(cls) without return types