code: def test_forward():
      """Check that the forward method works as expected."""
      classification_metric = BinaryAccuracy()
      regression_metric = MeanSquaredError()
      multitask_metrics = MultitaskWrapper(
          {
              "Classification": BinaryAccuracy(),
              "Regression": MeanSquaredError(),
          }
      )
  
      classification_results = classification_metric(
          _classification_preds, _classification_target
      )
      regression_results = regression_metric(
          _regression_preds, _regression_target
      )
      multitask_results = multitask_metrics(
          _multitask_preds, _multitask_targets
      )
  
      assert _dict_results_same_as_individual_results(
          classification_results, regression_results, multitask_results
      )
  
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 7 for calling a global function with example usage: test_forward() without return types