class_docstr: A ``TargetFormatter`` for targets that contain multiple string labels in a list.
  
  Examples
  ________
  
  .. doctest::
  
      >>> from flash.core.data.utilities.classification import MultiLabelTargetFormatter
      >>> formatter = MultiLabelTargetFormatter(labels=["bird", "cat", "dog"], num_classes=3)
      >>> formatter(["cat", "dog"])
      [0, 1, 1]
      >>> formatter(["bird"])
      [1, 0, 0]
class_docstr_tok: ["A","``","TargetFormatter","``","for","targets","that","contain","multiple","string","labels","in","a","list",".","Examples","________","..","doctest",":",":",">",">",">","from","flash.core.data.utilities.classification","import","MultiLabelTargetFormatter",">",">",">","formatter","=","MultiLabelTargetFormatter","(","labels=","[","``","bird","''",",","``","cat","''",",","``","dog","''","]",",","num_classes=3",")",">",">",">","formatter","(","[","``","cat","''",",","``","dog","''","]",")","[","0",",","1",",","1","]",">",">",">","formatter","(","[","``","bird","''","]",")","[","1",",","0",",","0","]"]
code: def format(self, target: Any) -> Any:
      result = [0] * self.num_classes
      for t in target:
          idx = super().format(t)
          result[idx] = 1
      return result
  
imports: from dataclasses import dataclass
  from functools import reduce
  from typing import Any, ClassVar, Dict, List, Optional, Tuple, Type, Union, cast
  import numpy
  import torch
  from torch import Tensor
  from flash.core.data.utilities.sort import sorted_alphanumeric
  from flash.core.utilities.imports import _TOPIC_CORE_AVAILABLE
label_desc: Use image node_id 1 for calling the MultiLabelTargetFormatter obj's underlying member method code with example usage: obj.format(target) and returns: result