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 predict_for_fit(self, input_data):
      output_type = input_data.data_type
      # if there is no need in fitting custom model and it is fit call
      if not self.model_fit:
          predict = input_data.features
          output_data = self._convert_to_output(
              input_data, predict=predict, data_type=output_type
          )
          return output_data
      else:
          return self.predict(input_data)
  
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 6 for calling the CustomModelImplementation obj's underlying member method code with example usage: obj.predict_for_fit(input_data) and returns: output_data, self