修改BucketedBatchSampler batch_idx_in_epoch 的计算方式，使其在分布式条件下可以正确地反应迭代次数

fastNLP/core/samplers/reproducible_batch_sampler.py

@@ -416,7 +416,7 @@ class BucketedBatchSampler(ReproducibleBatchSampler):
     @property
     def batch_idx_in_epoch(self):
         if self.drop_last:
-            return len(self.dataset) // self.batch_size - (len(self.dataset) - self.num_consumed_samples) // self.batch_size
+            return len(self.dataset) // self.num_replicas // self.batch_size - self.num_left_samples // self.batch_size
         else:
-            return (len(self.dataset) + self.batch_size - 1) // self.batch_size - \
-                   (len(self.dataset) - self.num_consumed_samples + self.batch_size - 1) // self.batch_size
+            return (len(self.dataset) // self.num_replicas + self.batch_size - 1) // self.batch_size - \
+                   (self.num_left_samples + self.batch_size - 1) // self.batch_size