code: def compare_min(values, weights):
      """Baseline implementation for min aggregation."""
      return np.min(values.numpy())
  
imports: import numpy
  import pytest
  import torch
  from torchmetrics.aggregation import CatMetric, MaxMetric, MeanMetric, MinMetric, SumMetric
  from torchmetrics.collections import MetricCollection
  from unittests import BATCH_SIZE, NUM_BATCHES
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 3 for calling a global function with example usage: compare_min(values, weights) and returns: np