diff --git a/egs/librispeech/ASR/pruned_transducer_stateless2/train.py b/egs/librispeech/ASR/pruned_transducer_stateless2/train.py
index ae45db60f..851822aae 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless2/train.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless2/train.py
@@ -450,9 +450,8 @@ def compute_loss(
             lm_scale=params.lm_scale,
             warmup_mode=warmup_mode,
         )
-        loss = params.simple_loss_scale * simple_loss
-        if not warmup_mode:
-            loss = loss + (pruned_loss * 0.01 if warmup_mode else pruned_loss)
+        loss = (params.simple_loss_scale * simple_loss +
+                (pruned_loss * 0.01 if warmup_mode else pruned_loss))
 
     assert loss.requires_grad == is_training
 
@@ -687,18 +686,8 @@ def run(rank, world_size, args):
         # Keep only utterances with duration between 1 second and 20 seconds
         return 1.0 <= c.duration <= 20.0
 
-    num_in_total = len(train_cuts)
-
     train_cuts = train_cuts.filter(remove_short_and_long_utt)
 
-    num_left = len(train_cuts)
-    num_removed = num_in_total - num_left
-    removed_percent = num_removed / num_in_total * 100
-
-    logging.info(f"Before removing short and long utterances: {num_in_total}")
-    logging.info(f"After removing short and long utterances: {num_left}")
-    logging.info(f"Removed {num_removed} utterances ({removed_percent:.5f}%)")
-
     train_dl = librispeech.train_dataloaders(train_cuts)
 
     valid_cuts = librispeech.dev_clean_cuts()