code: def test_basic_multitask():
      """Check that wrapping some Metrics in a MultitaskWrapper is the same as computing them individually."""
      classification_metric = BinaryAccuracy()
      regression_metric = MeanSquaredError()
      multitask_metrics = MultitaskWrapper(
          {
              "Classification": BinaryAccuracy(),
              "Regression": MeanSquaredError(),
          }
      )
  
      assert _multitask_same_as_individual_tasks(
          classification_metric, regression_metric, multitask_metrics
      )
  
file_path: torchmetrics/tests/unittests/wrappers/test_multitask.py
imports: import re
  import pytest
  import torch
  from torchmetrics import MetricCollection
  from torchmetrics.classification import BinaryAccuracy, BinaryF1Score
  from torchmetrics.regression import MeanAbsoluteError, MeanSquaredError
  from torchmetrics.wrappers import MultitaskWrapper
  from unittests import BATCH_SIZE, NUM_BATCHES
  from unittests.helpers import seed_all
label_desc: Use image node_id 5 for calling a global function with example usage: test_basic_multitask() without return types