code: def test_autocontrast_equal_minmax(device, dtype, channels):
      a = _create_data_batch(
          32, 32, num_samples=1, channels=channels, device=device
      )
      a = a / 2.0 + 0.3
      assert (F.autocontrast(a)[0] == F.autocontrast(a[0])).all()
  
      a[0, 0] = 0.7
      assert (F.autocontrast(a)[0] == F.autocontrast(a[0])).all()
  
imports: import colorsys
  import itertools
  import math
  import os
  from functools import partial
  from typing import Sequence
  import numpy
  import PIL.Image
  import pytest
  import torch
  import torchvision.transforms
  import torchvision.transforms._functional_pil
  import torchvision.transforms._functional_tensor
  import torchvision.transforms.functional
  from common_utils import _assert_approx_equal_tensor_to_pil, _assert_equal_tensor_to_pil, _create_data, _create_data_batch, _test_fn_on_batch, assert_equal, cpu_and_cuda, needs_cuda
  from torchvision.transforms import InterpolationMode
label_desc: Use image node_id 20 for calling a global function with example usage: test_autocontrast_equal_minmax(device, dtype, channels) without return types