diff --git a/examples/fairseq/models/bert.py b/examples/fairseq/models/bert.py
index f804973..c7c652d 100644
--- a/examples/fairseq/models/bert.py
+++ b/examples/fairseq/models/bert.py
@@ -130,6 +130,9 @@ class BertConfig(FairseqDataclass):
     tpu: bool = II("common.tpu")
     rel_pos_buckets: int = field(default=0, metadata={"help": ""})
     max_rel_pos: int = field(default=0, metadata={"help": ""})
+    use_xmoe: Optional[bool] = field(
+        default=False,
+    )
     moe_freq: int = field(
         default=0,
         metadata={"help": "Frequency at which we insert MoE Transformer layers"},
diff --git a/examples/fairseq/tasks/data/mlm_loader.py b/examples/fairseq/tasks/data/mlm_loader.py
index eb9cd72..510f654 100644
--- a/examples/fairseq/tasks/data/mlm_loader.py
+++ b/examples/fairseq/tasks/data/mlm_loader.py
@@ -166,6 +166,9 @@ class MLMLoader(BaseBatchGen):
             mlm_target_max_length = max([len(x[1]) for x in batch])
             s2s_source_max_length = max([len(x[2]) for x in batch])
             s2s_target_max_length = max([len(x[3]) for x in batch])
+            if self.args.pad_to_max_length:
+                mlm_source_max_length = self.args.tokens_per_sample
+                mlm_target_max_length = self.args.tokens_per_sample
 
             mlm_source_ids = np.full(
                 shape=(batch_size, mlm_source_max_length),
diff --git a/examples/fairseq/tasks/pretraining.py b/examples/fairseq/tasks/pretraining.py
index 2d32127..2022907 100644
--- a/examples/fairseq/tasks/pretraining.py
+++ b/examples/fairseq/tasks/pretraining.py
@@ -117,6 +117,9 @@ class PretrainingConfig(FairseqDataclass):
         default="",
         metadata={"help": ""},
     )
+    pad_to_max_length: bool = field(
+        default=False,
+        )
 
 
 @register_task("pretraining", dataclass=PretrainingConfig)