class_docstr: PredictionSingleton
code: def __init__(self, *args, **kwargs):
      if args:
          if len(args) > 1:
              raise ValueError(
                  "If a position argument is used, only 1 is allowed to set `actual_instance`"
              )
          if kwargs:
              raise ValueError(
                  "If a position argument is used, keyword arguments cannot be used."
              )
          super().__init__(actual_instance=args[0])
      else:
          super().__init__(**kwargs)
  
imports: from __future__ import annotations
  from inspect import getfullargspec
  import json
  import pprint
  import re
  from typing import Any, List, Optional
  from pydantic import BaseModel, Field, StrictStr, ValidationError, validator
  from lightly.openapi_generated.swagger_client.models.prediction_singleton_classification import PredictionSingletonClassification
  from lightly.openapi_generated.swagger_client.models.prediction_singleton_instance_segmentation import PredictionSingletonInstanceSegmentation
  from lightly.openapi_generated.swagger_client.models.prediction_singleton_keypoint_detection import PredictionSingletonKeypointDetection
  from lightly.openapi_generated.swagger_client.models.prediction_singleton_object_detection import PredictionSingletonObjectDetection
  from lightly.openapi_generated.swagger_client.models.prediction_singleton_semantic_segmentation import PredictionSingletonSemanticSegmentation
  from typing import Any, List
  from pydantic import StrictStr, Field, Extra
label_desc: Use image node_id 1 to create a new PredictionSingleton object from inherited base classes: BaseModel with example: obj = PredictionSingleton()