class_docstr: Assign class value from the labelmap.  This converts multi-dimension tensor to single scalar tensor.
  
  Args:
      offset: offset value to be added to the mask value to determine the final class
class_docstr_tok: ["Assign","class","value","from","the","labelmap",".","This","converts","multi-dimension","tensor","to","single","scalar","tensor",".","Args",":","offset",":","offset","value","to","be","added","to","the","mask","value","to","determine","the","final","class"]
code: def __init__(self, keys: KeysCollection, offset: int = -1) -> None:
      super().__init__(keys, allow_missing_keys=False)
      self.offset = offset
  
imports: from __future__ import annotations
  import math
  from typing import Any
  import numpy
  import torch
  from monai.config import KeysCollection, NdarrayOrTensor
  from monai.networks.layers import GaussianFilter
  from monai.transforms import MapTransform, Randomizable, SpatialPad
  from monai.utils import StrEnum, convert_to_numpy, optional_import
label_desc: Use image node_id 1 to create a new SetLabelClassd object from inherited base classes: MapTransform with example: obj = SetLabelClassd(keys, offset)