          # normalization
          if self._normalization == "instance":
              var_x = InstanceNormalization(name="{}_instancenorm".format(self._name))(var_x)
          if self._normalization == "batch":
              var_x = BatchNormalization(axis=3, name="{}_batchnorm".format(self._name))(var_x)
  
          # activation
          if self._activation == "leakyrelu":
              var_x = LeakyReLU(0.1, name="{}_leakyrelu".format(self._name))(var_x)
          if self._activation == "swish":
 
</s> remove             var_x = InstanceNormalization(name="{}_instancenorm".format(self._name))(var_x)
 </s> add             var_x = InstanceNormalization(name=f"{self._name}_instancenorm")(var_x) </s> remove             var_x = LeakyReLU(0.1, name="{}_leakyrelu".format(self._name))(var_x)
 </s> add             var_x = LeakyReLU(0.1, name=f"{self._name}_leakyrelu")(var_x) </s> remove             var_x = Swish(name="{}_swish".format(self._name))(var_x)
 </s> add             var_x = Swish(name=f"{self._name}_swish")(var_x) </s> remove                      name="{}_{}conv2d".format(self._name, "dw" if self._use_depthwise else ""),
 </s> add                      name=f"{self._name}_{'dw' if self._use_depthwise else ''}conv2d", </s> remove             var_x = Swish(name="{}_swish".format(self._name))(var_x)
 </s> add             var_x = Swish(name=f"{self._name}_swish")(var_x)
            var_x = BatchNormalization(axis=3, name=f"{self._name}_batchnorm")(var_x)
          # normalization
          if self._normalization == "instance":
              var_x = InstanceNormalization(name="{}_instancenorm".format(self._name))(var_x)
          if self._normalization == "batch":
            var_x = BatchNormalization(axis=3, name=f"{self._name}_batchnorm")(var_x)
  
          # activation
          if self._activation == "leakyrelu":
              var_x = LeakyReLU(0.1, name="{}_leakyrelu".format(self._name))(var_x)
          if self._activation == "swish":
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