code: def test_metrics_lambda_reset():
      m0 = ListGatherMetric(0)
      m1 = ListGatherMetric(1)
      m2 = ListGatherMetric(2)
      m0.update([1, 10, 100])
      m1.update([1, 10, 100])
      m2.update([1, 10, 100])
  
      def fn(x, y, z, t):
          return 1
  
      m = MetricsLambda(fn, m0, m1, z=m2, t=0)
  
      # initiating a new instance of MetricsLambda must reset
      # its argument metrics
      assert m0.list_ is None
      assert m1.list_ is None
      assert m2.list_ is None
  
      m0.update([1, 10, 100])
      m1.update([1, 10, 100])
      m2.update([1, 10, 100])
      m.reset()
      assert m0.list_ is None
      assert m1.list_ is None
      assert m2.list_ is None
  
imports: import os
  import numpy
  import pytest
  import torch
  from pytest import approx
  from sklearn.metrics import f1_score, precision_score, recall_score
  import ignite.distributed
  from ignite.engine import Engine
  from ignite.metrics import Accuracy, Metric, MetricsLambda, Precision, Recall
label_desc: Use image node_id 2 for calling a global function with example usage: test_metrics_lambda_reset() and returns: int