code: def _dict_results_same_as_individual_results(
      classification_results, regression_results, multitask_results
  ):
      return (
          multitask_results["Classification"] == classification_results
          and multitask_results["Regression"] == regression_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 1 for calling a global function with example usage: _dict_results_same_as_individual_results(classification_results, regression_results, multitask_results) and returns: unknown