          var_x = inputs
          filters = self._config["fs_original_min_filters"]
          for i in range(self._depth):
              name = f"fs_{'dny_' if self._is_alt else ''}enc"
              var_x = Conv2DBlock(filters,
                                  kernel_size=self._kernel_size,
                                  strides=self._strides,
                                  relu_alpha=self._relu_alpha,
 
</s> remove             var_x = Conv2DBlock(filters, activation="leakyrelu", name=f"fs_enc_convblk_{i}")(var_x)
 </s> add             name = f"fs_{'dny_' if self._is_alt else ''}enc"
            var_x = Conv2DBlock(filters,
                                kernel_size=self._kernel_size,
                                strides=self._strides,
                                relu_alpha=self._relu_alpha,
                                name=f"{name}_convblk_{i}")(var_x) </s> remove             var_x = LeakyReLU(alpha=0.1)(var_x)
 </s> add             if not self._is_dny:
                var_x = LeakyReLU(alpha=0.1)(var_x)
        if self._is_alt:
            var_x = Conv2DBlock(filters,
                                kernel_size=1,
                                strides=self._strides,
                                relu_alpha=self._relu_alpha)(var_x)

          var_x = inputs
          filters = self._config["fs_original_min_filters"]
        if self._is_alt:
            var_x = Conv2DBlock(filters,
                                kernel_size=1,
                                strides=self._strides,
                                relu_alpha=self._relu_alpha)(var_x)

          for i in range(self._depth):
              name = f"fs_{'dny_' if self._is_alt else ''}enc"
              var_x = Conv2DBlock(filters,
                                  kernel_size=self._kernel_size,
                                  strides=self._strides,
                                  relu_alpha=self._relu_alpha,
keep add keep keep keep keep keep keep
 Phaze-A - Updates for future implementations 
plugins/train/model/phaze_a.py