diff --git a/egs/librispeech/ASR/lstm_transducer_stateless/decode.py b/egs/librispeech/ASR/lstm_transducer_stateless/decode.py
index f7e3677da..00e906691 100755
--- a/egs/librispeech/ASR/lstm_transducer_stateless/decode.py
+++ b/egs/librispeech/ASR/lstm_transducer_stateless/decode.py
@@ -354,12 +354,12 @@ def decode_one_batch(
     supervisions = batch["supervisions"]
     feature_lens = supervisions["num_frames"].to(device)
 
-    feature_lens += params.left_context
-    feature = torch.nn.functional.pad(
-        feature,
-        pad=(0, 0, 0, params.left_context),
-        value=LOG_EPS,
-    )
+    # feature_lens += params.left_context
+    # feature = torch.nn.functional.pad(
+    #     feature,
+    #     pad=(0, 0, 0, params.left_context),
+    #     value=LOG_EPS,
+    # )
 
     encoder_out, encoder_out_lens = model.encoder(
         x=feature, x_lens=feature_lens
@@ -668,11 +668,6 @@ def main():
     params.unk_id = sp.piece_to_id("<unk>")
     params.vocab_size = sp.get_piece_size()
 
-    if params.simulate_streaming:
-        assert (
-            params.causal_convolution
-        ), "Decoding in streaming requires causal convolution"
-
     logging.info(params)
 
     logging.info("About to create model")
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless2/scaling.py b/egs/librispeech/ASR/pruned_transducer_stateless2/scaling.py
index 65c71ab2e..5f0785d91 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless2/scaling.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless2/scaling.py
@@ -409,8 +409,7 @@ class ScaledLSTM(nn.LSTM):
     def _reset_parameters(self, initial_speed: float):
         std = 0.1 / initial_speed
         a = (3 ** 0.5) * std
-        fan_in = self.input_size
-        scale = fan_in ** -0.5
+        scale = self.hidden_size ** -0.5
         v = scale / std
         for idx, name in enumerate(self._flat_weights_names):
             if "weight" in name: