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"]
code: def __init__(self, pipeline: "Pipeline" = None):
      self.total_pipeline_operations = Counter()
      self.operation_templates: List[OperationTemplate] = []
      self.unique_pipeline_id = str(uuid4())
      self.metadata: Dict[str, Any] = {}
      if pipeline is not None:
          self.depth = pipeline.depth
          self.metadata[
              "computation_time_in_seconds"
          ] = pipeline.computation_time
          self.metadata[
              "use_input_preprocessing"
          ] = pipeline.use_input_preprocessing
  
          # Save preprocessing operations
          self.data_preprocessor = pipeline.preprocessor
      else:
          self.depth = 0
          self.data_preprocessor = None
  
      self.log = default_log(self)
  
      self._pipeline_to_template(pipeline)
  
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 1 to create a new PipelineTemplate object  with example: obj = PipelineTemplate(pipeline)