      iterations: int
          The number of consecutive Conv2D layers to create
      """
      def __init__(self, level, filters, iterations):
          self._name = "conv{}_".format(level)
          self._level = level
          self._filters = filters
          self._iterator = range(1, iterations + 1)
  
      def __call__(self, inputs):
 
</s> remove         self._name = "conv{}_".format(level)
 </s> add         self._name = f"conv{level}_" </s> remove         self._name = "_pool{}".format(level)
 </s> add         self._name = f"_pool{level}" </s> remove         self._name = "_pool{}".format(level)
 </s> add         self._name = f"_pool{level}" </s> remove         self._name = _get_name("residual_{}".format(filters))
 </s> add         self._name = _get_name(f"residual_{filters}") </s> remove         self._name = _get_name("upscale_ri_{}".format(filters))
 </s> add         self._name = _get_name(f"upscale_ri_{filters}")
        self._name = f"conv{level}_"
      iterations: int
          The number of consecutive Conv2D layers to create
      """
      def __init__(self, level, filters, iterations):
        self._name = f"conv{level}_"
          self._level = level
          self._filters = filters
          self._iterator = range(1, iterations + 1)
  
      def __call__(self, inputs):
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) 
plugins/extract/mask/vgg_clear.py