          Any additional Keras standard layer keyword arguments to pass to the Convolutional 2D layer
      """
      def __init__(self, filters, kernel_size=3, padding="same", activation="leakyrelu",
                   interpolation="bilinear", sr_ratio=0.5, scale_factor=2, fast=False, **kwargs):
          self._name = _get_name("upscale2x_{}_{}".format(filters, "fast" if fast else "hyb"))
  
          self._fast = fast
          self._filters = filters if self._fast else filters - int(filters * sr_ratio)
          self._kernel_size = kernel_size
          self._padding = padding
 
</s> remove         self._name = _get_name("upscale_ri_{}".format(filters))
 </s> add         self._name = _get_name(f"upscale_ri_{filters}") </s> remove             "conv_output_{}".format(filters))
 </s> add             f"conv_output_{filters}") </s> remove         self._name = _get_name("separableconv2d_{}".format(filters))
 </s> add         self._name = _get_name(f"separableconv2d_{filters}") </s> remove         self._name = _get_name("residual_{}".format(filters))
 </s> add         self._name = _get_name(f"residual_{filters}") </s> remove         self._name = "conv{}_".format(level)
 </s> add         self._name = f"conv{level}_"
        self._name = _get_name(f"upscale2x_{filters}_{'fast' if fast else 'hyb'}")
          Any additional Keras standard layer keyword arguments to pass to the Convolutional 2D layer
      """
      def __init__(self, filters, kernel_size=3, padding="same", activation="leakyrelu",
                   interpolation="bilinear", sr_ratio=0.5, scale_factor=2, fast=False, **kwargs):
        self._name = _get_name(f"upscale2x_{filters}_{'fast' if fast else 'hyb'}")
  
          self._fast = fast
          self._filters = filters if self._fast else filters - int(filters * sr_ratio)
          self._kernel_size = kernel_size
          self._padding = padding
keep keep keep keep replace keep keep keep keep keep
 Update all Keras Imports to be conditional (#1214)

* Remove custom keras importer

* first round keras imports fix

* launcher.py: Remove KerasFinder references

* 2nd round keras imports update (lib and extract)

* 3rd round keras imports update (train)

* remove KerasFinder from tests

* 4th round keras imports update (tests) 
lib/model/nn_blocks.py