fix the bug of the ctc

fairseq/criterions/label_smoothed_cross_entropy_with_ctc.py

@@ -188,7 +188,8 @@ class LabelSmoothedCrossEntropyCriterionWithCTC(
 
         return loss
 
-    def reduce_metrics(self, logging_outputs) -> None:
+    @staticmethod
+    def reduce_metrics(logging_outputs) -> None:
         """Aggregate logging outputs from data parallel training."""
         loss_sum = utils.item(sum(log.get("loss", 0) for log in logging_outputs))
         trans_loss_sum = utils.item(
@@ -197,7 +198,6 @@ class LabelSmoothedCrossEntropyCriterionWithCTC(
         nll_loss_sum = utils.item(
             sum(log.get("nll_loss", 0) for log in logging_outputs)
         )
-        if self.ctc_weight > 0:
         ctc_loss_sum = utils.item(
             sum(log.get("ctc_loss", 0) for log in logging_outputs)
         )
@@ -215,7 +215,6 @@ class LabelSmoothedCrossEntropyCriterionWithCTC(
         metrics.log_scalar(
             "nll_loss", nll_loss_sum / ntokens / math.log(2), ntokens, round=3
         )
-        if self.ctc_weight > 0:
         metrics.log_scalar(
             "ctc_loss",
             ctc_loss_sum / sample_size / math.log(2),