code: def _dython_cramers_v(
      preds, target, bias_correction, nan_strategy, nan_replace_value
  ):
      preds = preds.argmax(1) if preds.ndim == 2 else preds
      target = target.argmax(1) if target.ndim == 2 else target
  
      v = dython_cramers_v(
          preds.numpy(),
          target.numpy(),
          bias_correction=bias_correction,
          nan_strategy=nan_strategy,
          nan_replace_value=nan_replace_value,
      )
      return torch.tensor(v)
  
file_path: torchmetrics/tests/unittests/nominal/test_cramers.py
imports: import itertools
  import operator
  from functools import partial
  import pytest
  import torch
  from dython.nominal import cramers_v
  from lightning_utilities.core.imports import compare_version
  from torchmetrics.functional.nominal.cramers import cramers_v, cramers_v_matrix
  from torchmetrics.nominal.cramers import CramersV
  from unittests import BATCH_SIZE, NUM_BATCHES, _Input
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 2 for calling a global function with example usage: _dython_cramers_v(preds, target, bias_correction, nan_strategy, nan_replace_value) and returns: torch