class_docstr: Pipeline wrapper with 'export_pipeline'/'import_pipeline' methods
  allowing user to upload a pipeline to JSON format and import it from JSON.
  
  :params pipeline: Pipeline object to export or empty Pipeline to import
class_docstr_tok: ["Pipeline","wrapper","with","'export_pipeline'\/'import_pipeline","'","methods","allowing","user","to","upload","a","pipeline","to","JSON","format","and","import","it","from","JSON",".",":","params","pipeline",":","Pipeline","object","to","export","or","empty","Pipeline","to","import"]
docstr: Create .pkl files for operations using absolute path 
docstr_tok: ["Create",".pkl","files","for","operations","using","absolute","path"]
code: def _create_fitted_operations(self, path=None):
      """Create .pkl files for operations using absolute path"""
      dict_fitted_operations = {}
      for operation in self.operation_templates:
          dict_fitted_operations[
              f"operation_{operation.operation_id}"
          ] = operation.export_operation(path)
  
      if all(val is None for val in dict_fitted_operations.values()):
          return None
  
      # Save preprocessing module
      preprocessing_path = self.export_preprocessing(path)
      if isinstance(preprocessing_path, str):
          preprocessing_splitted = os.path.split(preprocessing_path)
          preprocessing_path = [
              preprocessing_splitted[-2],
              preprocessing_splitted[-1],
          ]
      dict_fitted_operations["preprocessing"] = preprocessing_path
      return dict_fitted_operations
  
imports: import json
  import os
  from collections import Counter
  from datetime import datetime
  from io import BytesIO
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
  from uuid import uuid4
  import joblib
  import numpy
  from golem.core.log import default_log
  from fedot.core.operations.atomized_template import AtomizedModelTemplate
  from fedot.core.operations.operation_template import OperationTemplate, check_existing_path
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.repository.operation_types_repository import atomized_model_type
  from fedot.preprocessing.dummy_preprocessing import DummyPreprocessor
  from fedot.preprocessing.preprocessing import DataPreprocessor
label_desc: Use image node_id 6 for calling the PipelineTemplate obj's underlying member method code with example usage: obj._create_fitted_operations(path) and returns: dict_fitted_operations, None