                          get_backend().upper()) for v in _VALUES]
  
  
  def block_test(layer_func, kwargs={}, input_shape=None):
      """Test routine for a faceswaps neural network blocks.
  
      Tests are simple and are to ensure that the blocks compile on both tensorflow
      and plaidml backends
      """
      # generate input data
 
</s> remove _PARAMS = ["use_subpixel", "use_icnr_init", "use_convaware_init", "use_reflect_padding"]
 </s> add _PARAMS = ["use_icnr_init", "use_convaware_init", "use_reflect_padding"] </s> remove def test_blocks(use_subpixel, use_icnr_init, use_convaware_init, use_reflect_padding):
 </s> add def test_blocks(use_icnr_init, use_convaware_init, use_reflect_padding): </s> remove     if get_backend() == "amd" and use_subpixel:
        # Subpixel upscaling does not work on plaidml so skip this test
        pytest.skip("Subpixel upscaling not supported in plaidML")
    cls_ = NNBlocks(use_subpixel=use_subpixel,
                    use_icnr_init=use_icnr_init,
 </s> add     cls_ = NNBlocks(use_icnr_init=use_icnr_init, </s> remove         self.add_item(
            section=section, title="subpixel_upscaling", datatype=bool,
            default=False, group="network",
            info="Use subpixel upscaling rather than pixel shuffler. These techniques "
                 "are both designed to produce better resolving upscaling than other "
                 "methods. Each perform the same operations, but using different TF opts."
                 "\n\t https://arxiv.org/pdf/1609.05158.pdf")
 </s> add  </s> remove             # NB: Clipnorm is ballooning VRAM usage, which is not expected behavior
            # and may be a bug in Keras/TF.
            # PlaidML has a bug regarding the clipnorm parameter
 </s> add             # NB: Clip-norm is ballooning VRAM usage, which is not expected behavior
            # and may be a bug in Keras/Tensorflow.
            # PlaidML has a bug regarding the clip-norm parameter
    """Test routine for faceswap neural network blocks.
                          get_backend().upper()) for v in _VALUES]
  
  
  def block_test(layer_func, kwargs={}, input_shape=None):
    """Test routine for faceswap neural network blocks.
  
      Tests are simple and are to ensure that the blocks compile on both tensorflow
      and plaidml backends
      """
      # generate input data
keep keep keep keep replace keep keep keep keep keep
 Remove subpixel upscaling option (#1024) 
tests/lib/model/nn_blocks_test.py