class_docstr: Meter to calculate mean AP metric for multi-label image classification task
  on multiple output single target.
  
  Supports Single target and multiple output. A list of mean AP meters is
  constructed and each output has a meter associated.
  
  Args:
      meters_config (AttrDict): config containing the meter settings
  
  meters_config should specify the num_meters and meter_names
class_docstr_tok: ["Meter","to","calculate","mean","AP","metric","for","multi-label","image","classification","task","on","multiple","output","single","target",".","Supports","Single","target","and","multiple","output",".","A","list","of","mean","AP","meters","is","constructed","and","each","output","has","a","meter","associated",".","Args",":","meters_config","(","AttrDict",")",":","config","containing","the","meter","settings","meters_config","should","specify","the","num_meters","and","meter_names"]
docstr: Updates the value of the meter for the given model output list and targets.
  
  Args:
      model_output: list of tensors of shape (B, C) where each value is
                    either logit or class probability.
      target:       tensor of shape (B).
  
  NOTE: For binary classification, C=2.
docstr_tok: ["Updates","the","value","of","the","meter","for","the","given","model","output","list","and","targets",".","Args",":","model_output",":","list","of","tensors","of","shape","(","B",",","C",")","where","each","value","is","either","logit","or","class","probability",".","target",":","tensor","of","shape","(","B",")",".","NOTE",":","For","binary","classification",",","C=2","."]
code: def update(
      self,
      model_output: Union[torch.Tensor, List[torch.Tensor]],
      target: torch.Tensor,
  ):
      """
      Updates the value of the meter for the given model output list and targets.
  
      Args:
          model_output: list of tensors of shape (B, C) where each value is
                        either logit or class probability.
          target:       tensor of shape (B).
  
      NOTE: For binary classification, C=2.
      """
      if isinstance(model_output, torch.Tensor):
          model_output = [model_output]
      assert isinstance(model_output, list)
      assert len(model_output) == self._num_meters
      for meter, output in zip(self._meters, model_output):
          probs = torch.nn.Sigmoid()(output)
          meter.update(probs, target)
  
imports: import pprint
  from typing import List, Union
  import torch
  from classy_vision.generic.util import is_pos_int
  from classy_vision.meters import ClassyMeter, register_meter
  from vissl.config import AttrDict
  from vissl.meters.mean_ap_meter import MeanAPMeter
label_desc: Use image node_id 9 for calling the MeanAPListMeter obj's underlying member method code with example usage: obj.update(model_output, target) without return types