chatlearn/utils/vllm_utils.py [210:229]:
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            ],
            "layer_re": self.layer_re
        }
        super().__init__(src_names, layer_offset)

    def map_src_to_dst(self):
        for src_name in self.src_names:
            # convert word embeddings.
            if src_name in self.embedding_sync_map:
                self._dst_names.append(self.get_dst_name(self.embedding_sync_map, src_name))
                continue

            # final layer
            if src_name in self.final_layer_sync_map:
                self._dst_names.append(self.get_dst_name(self.final_layer_sync_map, src_name))
                continue

            m = self.layer_re.match(src_name)
            # Stop if that's not a layer
            if m is None:
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chatlearn/utils/vllm_utils.py [298:317]:
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            ],
            "layer_re": self.layer_re
        }
        super().__init__(src_names, layer_offset)

    def map_src_to_dst(self):
        for src_name in self.src_names:
             # convert word embeddings.
            if src_name in self.embedding_sync_map:
                self._dst_names.append(self.get_dst_name(self.embedding_sync_map, src_name))
                continue

            # final layer
            if src_name in self.final_layer_sync_map:
                self._dst_names.append(self.get_dst_name(self.final_layer_sync_map, src_name))
                continue

            m = self.layer_re.match(src_name)
            # Stop if that's not a layer
            if m is None:
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