      """
      def __init__(self, *args, padding="same", check_icnr_init=False, **kwargs):
          if kwargs.get("name", None) is None:
              filters = kwargs["filters"] if "filters" in kwargs else args[0]
              kwargs["name"] = _get_name("conv2d_{}".format(filters))
          initializer = _get_default_initializer(kwargs.pop("kernel_initializer", None))
          if check_icnr_init and _CONFIG["icnr_init"]:
              initializer = ICNR(initializer=initializer)
              logger.debug("Using ICNR Initializer: %s", initializer)
          super().__init__(*args, padding=padding, kernel_initializer=initializer, **kwargs)
 
</s> remove             "conv_output_{}".format(filters))
 </s> add             f"conv_output_{filters}") </s> remove         self._name = _get_name("upscale2x_{}_{}".format(filters, "fast" if fast else "hyb"))
 </s> add         self._name = _get_name(f"upscale2x_{filters}_{'fast' if fast else 'hyb'}") </s> remove         self._name = _get_name("residual_{}".format(filters))
 </s> add         self._name = _get_name(f"residual_{filters}") </s> remove         self._name = kwargs.pop("name") if "name" in kwargs else _get_name(
            "conv_{}".format(filters))
 </s> add         self._name = kwargs.pop("name") if "name" in kwargs else _get_name(f"conv_{filters}") </s> remove         self._name = _get_name("upscale_ri_{}".format(filters))
 </s> add         self._name = _get_name(f"upscale_ri_{filters}")
            kwargs["name"] = _get_name(f"conv2d_{filters}")
      """
      def __init__(self, *args, padding="same", check_icnr_init=False, **kwargs):
          if kwargs.get("name", None) is None:
              filters = kwargs["filters"] if "filters" in kwargs else args[0]
            kwargs["name"] = _get_name(f"conv2d_{filters}")
          initializer = _get_default_initializer(kwargs.pop("kernel_initializer", None))
          if check_icnr_init and _CONFIG["icnr_init"]:
              initializer = ICNR(initializer=initializer)
              logger.debug("Using ICNR Initializer: %s", initializer)
          super().__init__(*args, padding=padding, kernel_initializer=initializer, **kwargs)
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