class_docstr: Inference Task
class_docstr_tok: ["Inference","Task"]
docstr: :param type: Type of Infer (segmentation, deepgrow etc..)
  :param labels: Labels associated to this Infer
  :param dimension: Input dimension
  :param description: Description
  :param config: K,V pairs to be part of user config
docstr_tok: [":","param","type",":","Type","of","Infer","(","segmentation",",","deepgrow","etc","..",")",":","param","labels",":","Labels","associated","to","this","Infer",":","param","dimension",":","Input","dimension",":","param","description",":","Description",":","param","config",":","K",",","V","pairs","to","be","part","of","user","config"]
code: def __init__(
      self,
      type: Union[str, InferType],
      labels: Union[str, None, Sequence[str], Dict[Any, Any]],
      dimension: int,
      description: str,
      config: Union[None, Dict[str, Any]] = None,
  ):
      """
      :param type: Type of Infer (segmentation, deepgrow etc..)
      :param labels: Labels associated to this Infer
      :param dimension: Input dimension
      :param description: Description
      :param config: K,V pairs to be part of user config
      """
  
      self.type = type
      self.labels = (
          []
          if labels is None
          else [labels]
          if isinstance(labels, str)
          else labels
      )
      self.dimension = dimension
      self.description = description
  
      self._config: Dict[str, Any] = {}
      if config:
          self._config.update(config)
  
file_path: MONAILabel/monailabel/interfaces/tasks/infer_v2.py
imports: import logging
  from abc import ABCMeta, abstractmethod
  from enum import Enum
  from typing import Any, Dict, Sequence, Tuple, Union
label_desc: Use image node_id 1 to create a new InferTask object  with example: obj = InferTask(type, labels, dimension, description, config)