code: def test_flatten_list():
      """Check that _flatten utility function works as expected."""
      inp = [[1, 2, 3], [4, 5], [6]]
      out = _flatten(inp)
      assert out == [1, 2, 3, 4, 5, 6]
  
imports: import sys
  import numpy
  import pytest
  import torch
  from torch import tensor
  from torchmetrics.regression import MeanSquaredError, PearsonCorrCoef
  from torchmetrics.utilities import check_forward_full_state_property, rank_zero_debug, rank_zero_info, rank_zero_warn
  from torchmetrics.utilities.checks import _allclose_recursive
  from torchmetrics.utilities.data import _bincount, _cumsum, _flatten, _flatten_dict, select_topk, to_categorical, to_onehot
  from torchmetrics.utilities.distributed import class_reduce, reduce
  from torchmetrics.utilities.exceptions import TorchMetricsUserWarning
  from torchmetrics.utilities.imports import _TORCH_GREATER_EQUAL_1_13
label_desc: Use image node_id 6 for calling a global function with example usage: test_flatten_list() without return types