class_docstr: Implementation of container for custom model, which is presented as function with
  input train_data(np.array), test_data(np.array), parameters(dict)
  output type specification DataTypesEnum (string - 'ts', 'table', 'image', 'text')
  into parameters dictionary {'model_predict': function, 'model_fit': function}
class_docstr_tok: ["Implementation","of","container","for","custom","model",",","which","is","presented","as","function","with","input","train_data","(","np.array",")",",","test_data","(","np.array",")",",","parameters","(","dict",")","output","type","specification","DataTypesEnum","(","string","-","'ts","'",",","'table","'",",","'image","'",",","'text","'",")","into","parameters","dictionary","{","'model_predict","'",":","function",",","'model_fit","'",":","function","}"]
code: def model_fit(self) -> Optional[Callable]:
      # custom model can be without fitting
      model_fit = None
      if "model_fit" in self.params.keys():
          model_fit = self.params.get("model_fit")
          if not isinstance(model_fit, Callable):
              raise ValueError("Input model is not Callable")
      return model_fit
  
file_path: FEDOT/fedot/core/operations/evaluation/operation_implementations/models/custom_model.py
imports: from typing import Callable, Optional
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import ModelImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.repository.dataset_types import DataTypesEnum
label_desc: Use image node_id 3 for calling the CustomModelImplementation obj's underlying member method code with example usage: obj.model_fit() and returns: model_fit