code: def test_PatientMetricAttentiveScheduler(
      base_lr, decay_factor, patience, minimum_lr, seq_loss_lr
  ):
      lr_scheduler = lrs.MetricAttentiveScheduler(
          learning_rate=base_lr,
          decay_factor=decay_factor,
          patience=lrs.Patience(patience, lrs.Min()),
          min_learning_rate=minimum_lr,
      )
  
      for loss, lr_exp in seq_loss_lr:
          lr_scheduler.step(loss)
          assert np.isclose(lr_scheduler.learning_rate, lr_exp)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_PatientMetricAttentiveScheduler(base_lr, decay_factor, patience, minimum_lr, seq_loss_lr) without return types