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 __init__(self, params: Optional[OperationParameters] = None):
      super().__init__(params)
      if not self.params:
          raise ValueError(
              "There is no specified parameters for custom model!"
          )
      self.fitted_model = None
  
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 1 to create a new CustomModelImplementation object from inherited base classes: ModelImplementation with example: obj = CustomModelImplementation(params)