class_docstr: Meter to calculate top-k accuracy for single label image classification task.
  
  Supports multi-target and multiple output. A list of accuracy meters is
  constructed and each output has a meter associated.
  
  Example:
      target = [0 0 0 1 1]  # Correct classes are 0, 3
  
      pred = [0.06, 0.41, 0.04, 0.39, 0.1]  # Top-1 prediction is 1, top-3 is 1, 3, 0
  
      Accuracy@1: 0 correct = 0.0
      Accuracy@3: 1 correct = 1.0
  
  Args:
      num_meters: number of meters and hence we have same number of outputs
      topk_values: list of int `k` values. Example: [1, 5]
      meter_names: list of str indicating the name of meter. Usually corresponds
                   to the output layer name.
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docstr: Reset all the meters
docstr_tok: ["Reset","all","the","meters"]
code: def reset(self):
      """
      Reset all the meters
      """
      [x.reset() for x in self._meters]
  
imports: import pprint
  from typing import List, Union
  import torch
  import torch.nn.functional
  from classy_vision.generic.util import is_pos_int
  from classy_vision.meters import AccuracyMeter, ClassyMeter, register_meter
  from vissl.config import AttrDict
  from vissl.losses.cross_entropy_multiple_output_single_target import EnsembleOutput
label_desc: Use image node_id 11 for calling the AccuracyListMeter obj's underlying member method code with example usage: obj.reset() without return types