diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train.py.swp
index f60604e52..a7e3822a3 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py
index ee57ec55a..a7bea4a07 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py
@@ -1064,24 +1064,24 @@ def train_one_epoch(
                 wb.log({"train/loss": loss_info["loss"]*numel})
 
 
-        if batch_idx % params.valid_interval == 0 and not params.print_diagnostics:
-            logging.info("Computing validation loss")
-            valid_info = compute_validation_loss(
-                params=params,
-                model=model,
-                sp=sp,
-                valid_dl=valid_dl,
-                world_size=world_size,
-            )
-            model.train()
-            logging.info(f"Epoch {params.cur_epoch}, validation: {valid_info}")
-            logging.info(
-                f"Maximum memory allocated so far is {torch.cuda.max_memory_allocated()//1000000}MB"
-            )
-            if tb_writer is not None:
-                valid_info.write_summary(
-                    tb_writer, "train/valid_", params.batch_idx_train
-                )
+#if batch_idx % params.valid_interval == 0 and not params.print_diagnostics:
+    logging.info("Computing validation loss")
+    valid_info = compute_validation_loss(
+        params=params,
+        model=model,
+        sp=sp,
+        valid_dl=valid_dl,
+        world_size=world_size,
+    )
+    model.train()
+    logging.info(f"Epoch {params.cur_epoch}, validation: {valid_info}")
+    logging.info(
+        f"Maximum memory allocated so far is {torch.cuda.max_memory_allocated()//1000000}MB"
+    )
+    if tb_writer is not None:
+        valid_info.write_summary(
+            tb_writer, "train/valid_", params.batch_idx_train
+        )
 
     loss_value = tot_loss["loss"] / tot_loss["frames"]
     params.train_loss = loss_value