update author info

egs/librispeech/ASR/lstm_transducer_stateless2/decode.py

@@ -1,7 +1,8 @@
 #!/usr/bin/env python3
 #
 # Copyright 2021-2022 Xiaomi Corporation (Author: Fangjun Kuang,
-#                                                 Zengwei Yao)
+#                                                 Zengwei Yao,
+#                                                 Xiaoyu Yang)
 #
 # See ../../../../LICENSE for clarification regarding multiple authors
 #
@@ -91,7 +92,7 @@ Usage:
     --beam 20.0 \
     --max-contexts 8 \
     --max-states 64
-    
+
 (8) modified beam search (with RNNLM shallow fusion)
 ./lstm_transducer_stateless2/decode.py \
     --epoch 35 \
@@ -105,7 +106,7 @@ Usage:
     --rnn-lm-epoch 99 \
     --rnn-lm-avg 1 \
     --rnn-lm-num-layers 3 \
-    --rnn-lm-tie-weights 1   
+    --rnn-lm-tie-weights 1
 """
 
 
@@ -131,7 +132,6 @@ from beam_search import (
     greedy_search_batch,
     modified_beam_search,
     modified_beam_search_rnnlm_shallow_fusion,
-    
 )
 from librispeech import LibriSpeech
 from train import add_model_arguments, get_params, get_transducer_model
@@ -386,11 +386,7 @@ def get_parser():
         last output linear layer
         """,
     )
-    parser.add_argument(
-        "--ilm-scale",
-        type=float,
-        default=-0.1
-    )
+    parser.add_argument("--ilm-scale", type=float, default=-0.1)
     add_model_arguments(parser)
 
     return parser
@@ -642,9 +638,13 @@ def decode_dataset(
     for batch_idx, batch in enumerate(dl):
         texts = batch["supervisions"]["text"]
         cut_ids = [cut.id for cut in batch["supervisions"]["cut"]]
-        total_duration = sum([cut.duration for cut in batch["supervisions"]["cut"]])
-        
-        logging.info(f"Decoding {batch_idx}-th batch, batch size is {len(cut_ids)}, total duration is {total_duration}")
+        total_duration = sum(
+            [cut.duration for cut in batch["supervisions"]["cut"]]
+        )
+
+        logging.info(
+            f"Decoding {batch_idx}-th batch, batch size is {len(cut_ids)}, total duration is {total_duration}"
+        )
 
         hyps_dict = decode_one_batch(
             params=params,
@@ -765,10 +765,10 @@ def main():
     else:
         params.suffix += f"-context-{params.context_size}"
         params.suffix += f"-max-sym-per-frame-{params.max_sym_per_frame}"
-    
+
     if "rnnlm" in params.decoding_method:
         params.suffix += f"-rnnlm-lm-scale-{params.rnn_lm_scale}"
-    
+
     if "ILME" in params.decoding_method:
         params.suffix += f"-ILME-scale={params.ilm_scale}"
 
@@ -903,7 +903,7 @@ def main():
         )
         rnn_lm_model.to(device)
         rnn_lm_model.eval()
-    
+
     else:
         rnn_lm_model = None