class_docstr: Meter to calculate mean AP metric for multi-label image classification task.
  
  Args:
      meters_config (AttrDict): config containing the meter settings
  
  meters_config should specify the num_classes
class_docstr_tok: ["Meter","to","calculate","mean","AP","metric","for","multi-label","image","classification","task",".","Args",":","meters_config","(","AttrDict",")",":","config","containing","the","meter","settings","meters_config","should","specify","the","num_classes"]
docstr: Reset the meter
docstr_tok: ["Reset","the","meter"]
code: def reset(self):
      """
      Reset the meter
      """
      self._scores = torch.zeros(
          0, self.num_classes, dtype=torch.float32
      )
      self._targets = torch.zeros(0, self.num_classes, dtype=torch.int8)
      self._total_sample_count = torch.zeros(1)
      self._curr_sample_count = torch.zeros(1)
  
imports: import logging
  import numpy
  import torch
  from classy_vision.generic.distributed_util import all_reduce_sum, gather_from_all
  from classy_vision.meters import ClassyMeter, register_meter
  from vissl.config import AttrDict
  from vissl.utils.env import get_machine_local_and_dist_rank
  from vissl.utils.svm_utils.evaluate import get_precision_recall
label_desc: Use image node_id 8 for calling the MeanAPMeter obj's underlying member method code with example usage: obj.reset() without return types