          """
          name = "conv{}".format(idx)
          var_x = inputs
          for i in range(1, 3):
              rec_name = "{}_{}".format(name, i)
              size = 1 if i == 1 else 3
              if i == 2:
                  var_x = ZeroPadding2D(1, name="{}.zeropad".format(rec_name))(var_x)
              var_x = Conv2D(filters * i,
                             kernel_size=size,
 
</s> remove                 var_x = ZeroPadding2D(1, name="{}.zeropad".format(rec_name))(var_x)
 </s> add                 var_x = ZeroPadding2D(1, name=f"{rec_name}.zeropad")(var_x) </s> remove         name = "conv{}".format(idx)
 </s> add         name = f"conv{idx}" </s> remove             rec_name = "{}_{}".format(name, i)
            var_x = ZeroPadding2D(1, name="{}.zeropad".format(rec_name))(var_x)
 </s> add             rec_name = f"{name}_{i}"
            var_x = ZeroPadding2D(1, name=f"{rec_name}.zeropad")(var_x) </s> remove         name = "conv{}".format(idx)
 </s> add         name = f"conv{idx}" </s> remove         retval = list()
 </s> add         retval = []
            rec_name = f"{name}_{i}"
          """
          name = "conv{}".format(idx)
          var_x = inputs
          for i in range(1, 3):
            rec_name = f"{name}_{i}"
              size = 1 if i == 1 else 3
              if i == 2:
                  var_x = ZeroPadding2D(1, name="{}.zeropad".format(rec_name))(var_x)
              var_x = Conv2D(filters * i,
                             kernel_size=size,
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/detect/s3fd.py