old_contents: import eagerpy as ep
  import numpy as np
  import pytest
  from typing import Any
  
  from foolbox.attacks.gen_attack_utils import rescale_images
  
  
  def test_rescale_axis(request: Any, dummy: ep.Tensor) -> None:
      backend = request.config.option.backend
      if backend == "numpy":
          pytest.skip()
  
      x_np = np.random.uniform(0.0, 1.0, size=(16, 3, 64, 64))
      x_np_ep = ep.astensor(x_np)
      x_up_np_ep = rescale_images(x_np_ep, (16, 3, 128, 128), 1)
      x_up_np = x_up_np_ep.numpy()
  
      x = ep.from_numpy(dummy, x_np)
      x_ep = ep.astensor(x)
      x_up_ep = rescale_images(x_ep, (16, 3, 128, 128), 1)
      x_up = x_up_ep.numpy()
  
      assert np.allclose(x_up_np, x_up)
  
  
  def test_rescale_axis_nhwc(request: Any, dummy: ep.Tensor) -> None:
      backend = request.config.option.backend
      if backend == "numpy":
          pytest.skip()
  
      x_np = np.random.uniform(0.0, 1.0, size=(16, 64, 64, 3))
      x_np_ep = ep.astensor(x_np)
      x_up_np_ep = rescale_images(x_np_ep, (16, 128, 128, 3), -1)
      x_up_np = x_up_np_ep.numpy()
  
      x = ep.from_numpy(dummy, x_np)
      x_ep = ep.astensor(x)
      x_up_ep = rescale_images(x_ep, (16, 128, 128, 3), -1)
      x_up = x_up_ep.numpy()
  
      assert np.allclose(x_up_np, x_up)
  
new_contents: import eagerpy as ep
  import numpy as np
  import pytest
  from typing import Any
  
  from foolbox.attacks.gen_attack_utils import rescale_images
  
  
  def test_rescale_axis(request: Any, dummy: ep.Tensor) -> None:
      backend = request.config.option.backend
      if backend == "numpy":
          pytest.skip()
  
      x_np = np.random.uniform(0.0, 1.0, size=(16, 3, 64, 64))
      x_np_ep = ep.astensor(x_np)
      x_up_np_ep = rescale_images(x_np_ep, (16, 3, 128, 128), 1)
      x_up_np = x_up_np_ep.numpy()
  
      x = ep.from_numpy(dummy, x_np)
      x_ep = ep.astensor(x)
      x_up_ep = rescale_images(x_ep, (16, 3, 128, 128), 1)
      x_up = x_up_ep.numpy()
  
      assert np.allclose(x_up_np, x_up, atol=1e-5)
  
  
  def test_rescale_axis_nhwc(request: Any, dummy: ep.Tensor) -> None:
      backend = request.config.option.backend
      if backend == "numpy":
          pytest.skip()
  
      x_np = np.random.uniform(0.0, 1.0, size=(16, 64, 64, 3))
      x_np_ep = ep.astensor(x_np)
      x_up_np_ep = rescale_images(x_np_ep, (16, 128, 128, 3), -1)
      x_up_np = x_up_np_ep.numpy()
  
      x = ep.from_numpy(dummy, x_np)
      x_ep = ep.astensor(x)
      x_up_ep = rescale_images(x_ep, (16, 128, 128, 3), -1)
      x_up = x_up_ep.numpy()
  
      assert np.allclose(x_up_np, x_up, atol=1e-5)
  
subject: Make assert comparison less strict due to dtype differences