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modeling_indictrans.py

@@ -801,6 +801,12 @@ class IndicTransDecoder(IndicTransPreTrainedModel):
         # Initialize weights and apply final processing
         self.post_init()
 
+    def get_input_embeddings(self):
+        return self.embed_tokens.word_embeddings
+
+    def set_input_embeddings(self, value):
+        self.embed_tokens.word_embeddings = value
+
     def forward(
             self,
             input_ids: Optional[torch.Tensor] = None,
@@ -1194,11 +1200,11 @@ class IndicTransForConditionalGeneration(IndicTransPreTrainedModel):
         """
         return_dict = return_dict if return_dict is not None else self.config.use_return_dict
 
-        if labels is not None:
-            if decoder_input_ids is None:
-                decoder_input_ids = shift_tokens_right(
-                    labels, self.config.pad_token_id, self.config.decoder_start_token_id
-                )
+        # if labels is not None:
+        #     if decoder_input_ids is None:
+        #         decoder_input_ids = shift_tokens_right(
+        #             labels, self.config.pad_token_id, self.config.decoder_start_token_id
+        #         )
 
         outputs = self.model(
             input_ids,