code: def test_metric_collection_repr():
      """Test MetricCollection."""
  
      class A(DummyMetricSum):
          pass
  
      class B(DummyMetricDiff):
          pass
  
      m1 = A()
      m2 = B()
      metric_collection = MetricCollection(
          [m1, m2], prefix=None, postfix=None
      )
  
      expected = "MetricCollection(\n  (A): A()\n  (B): B()\n)"
      assert metric_collection.__repr__() == expected
  
      metric_collection = MetricCollection(
          [m1, m2], prefix="a", postfix=None
      )
  
      expected = (
          "MetricCollection(\n  (A): A()\n  (B): B(),\n  prefix=a\n)"
      )
      assert metric_collection.__repr__() == expected
  
      metric_collection = MetricCollection(
          [m1, m2], prefix=None, postfix="a"
      )
      expected = (
          "MetricCollection(\n  (A): A()\n  (B): B(),\n  postfix=a\n)"
      )
      assert metric_collection.__repr__() == expected
  
      metric_collection = MetricCollection(
          [m1, m2], prefix="a", postfix="b"
      )
      expected = "MetricCollection(\n  (A): A()\n  (B): B(),\n  prefix=a,\n  postfix=b\n)"
      assert metric_collection.__repr__() == expected
  
imports: import pickle
  from copy import deepcopy
  from typing import Any
  import pytest
  import torch
  from torchmetrics import Metric, MetricCollection
  from torchmetrics.classification import BinaryAccuracy, MulticlassAccuracy, MulticlassAUROC, MulticlassAveragePrecision, MulticlassCohenKappa, MulticlassConfusionMatrix, MulticlassF1Score, MulticlassMatthewsCorrCoef, MulticlassPrecision, MulticlassRecall, MultilabelAUROC, MultilabelAveragePrecision
  from torchmetrics.utilities.checks import _allclose_recursive
  from unittests.helpers import seed_all
  from unittests.helpers.testers import DummyMetricDiff, DummyMetricMultiOutputDict, DummyMetricSum
label_desc: Use image node_id 6 for calling a global function with example usage: test_metric_collection_repr() without return types