class_docstr: Abstract base class for all data formatters.
  
  User can implement the abstract methods below to perform dataset-specific
  manipulations.
class_docstr_tok: ["Abstract","base","class","for","all","data","formatters",".","User","can","implement","the","abstract","methods","below","to","perform","dataset-specific","manipulations","."]
docstr: Returns fixed model parameters for experiments.
docstr_tok: ["Returns","fixed","model","parameters","for","experiments","."]
code: def get_experiment_params(self):
      """Returns fixed model parameters for experiments."""
  
      required_keys = [
          "total_time_steps",
          "num_encoder_steps",
          "num_epochs",
          "early_stopping_patience",
          "multiprocessing_workers",
      ]
  
      fixed_params = self.get_fixed_params()
  
      for k in required_keys:
          if k not in fixed_params:
              raise ValueError(
                  "Field {}".format(k)
                  + " missing from fixed parameter definitions!"
              )
  
      fixed_params["column_definition"] = self.get_column_definition()
  
      fixed_params.update(self._get_tft_input_indices())
  
      return fixed_params
  
file_path: qlib/examples/benchmarks/TFT/data_formatters/base.py
imports: import abc
  import enum
label_desc: Use image node_id 12 for calling the GenericDataFormatter obj's underlying member method code with example usage: obj.get_experiment_params() and returns: fixed_params