modify pretrained.py

egs/librispeech/ASR/lstm_transducer_stateless/export.py

@@ -358,9 +358,9 @@ def main():
 
     model.to("cpu")
     model.eval()
-    convert_scaled_to_non_scaled(model, inplace=True)
 
     if params.jit_trace is True:
+        convert_scaled_to_non_scaled(model, inplace=True)
         logging.info("Using torch.jit.trace()")
         encoder_filename = params.exp_dir / "encoder_jit_trace.pt"
         export_encoder_model_jit_trace(model.encoder, encoder_filename)

egs/librispeech/ASR/lstm_transducer_stateless/pretrained.py

@@ -18,16 +18,16 @@
 Usage:
 
 (1) greedy search
-./pruned_transducer_stateless2/pretrained.py \
-    --checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
+./lstm_transducer_stateless/pretrained.py \
+    --checkpoint ./lstm_transducer_stateless/exp/pretrained.pt \
     --bpe-model ./data/lang_bpe_500/bpe.model \
     --method greedy_search \
     /path/to/foo.wav \
     /path/to/bar.wav
 
 (2) beam search
-./pruned_transducer_stateless2/pretrained.py \
-    --checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
+./lstm_transducer_stateless/pretrained.py \
+    --checkpoint ./lstm_transducer_stateless/exp/pretrained.pt \
     --bpe-model ./data/lang_bpe_500/bpe.model \
     --method beam_search \
     --beam-size 4 \
@@ -35,8 +35,8 @@ Usage:
     /path/to/bar.wav
 
 (3) modified beam search
-./pruned_transducer_stateless2/pretrained.py \
-    --checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
+./lstm_transducer_stateless/pretrained.py \
+    --checkpoint ./lstm_transducer_stateless/exp/pretrained.pt \
     --bpe-model ./data/lang_bpe_500/bpe.model \
     --method modified_beam_search \
     --beam-size 4 \
@@ -44,18 +44,18 @@ Usage:
     /path/to/bar.wav
 
 (4) fast beam search
-./pruned_transducer_stateless2/pretrained.py \
-    --checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
+./lstm_transducer_stateless/pretrained.py \
+    --checkpoint ./lstm_transducer_stateless/exp/pretrained.pt \
     --bpe-model ./data/lang_bpe_500/bpe.model \
     --method fast_beam_search \
     --beam-size 4 \
     /path/to/foo.wav \
     /path/to/bar.wav
 
-You can also use `./pruned_transducer_stateless2/exp/epoch-xx.pt`.
+You can also use `./lstm_transducer_stateless/exp/epoch-xx.pt`.
 
-Note: ./pruned_transducer_stateless2/exp/pretrained.pt is generated by
-./pruned_transducer_stateless2/export.py
+Note: ./lstm_transducer_stateless/exp/pretrained.pt is generated by
+./lstm_transducer_stateless/export.py
 """
 
 
@@ -77,7 +77,7 @@ from beam_search import (
     modified_beam_search,
 )
 from torch.nn.utils.rnn import pad_sequence
-from train import get_params, get_transducer_model
+from train import add_model_arguments, get_params, get_transducer_model
 
 
 def get_parser():
@@ -178,6 +178,8 @@ def get_parser():
         """,
     )
 
+    add_model_arguments(parser)
+
     return parser
 
 
@@ -268,7 +270,7 @@ def main():
 
     feature_lengths = torch.tensor(feature_lengths, device=device)
 
-    encoder_out, encoder_out_lens = model.encoder(
+    encoder_out, encoder_out_lens, _ = model.encoder(
         x=features, x_lens=feature_lengths
     )
 

egs/librispeech/ASR/lstm_transducer_stateless/train.py

@@ -111,9 +111,10 @@ def add_model_arguments(parser: argparse.ArgumentParser):
     parser.add_argument(
         "--aux-layer-period",
         type=int,
-        default=3,
+        default=0,
         help="""Peroid of auxiliary layers used for randomly combined during training.
-        If not larger than 0 (e.g., -1), will not use the random combiner.
+        If set to 0, will not use the random combiner (Default).
+        You can set a positive integer to use the random combiner, e.g., 3.
         """,
     )
 
@@ -206,7 +207,7 @@ def get_parser():
     parser.add_argument(
         "--lr-epochs",
         type=float,
-        default=6,
+        default=10,
         help="""Number of epochs that affects how rapidly the learning rate decreases.
         """,
     )
@@ -270,7 +271,7 @@ def get_parser():
     parser.add_argument(
         "--save-every-n",
         type=int,
-        default=8000,
+        default=4000,
         help="""Save checkpoint after processing this number of batches"
         periodically. We save checkpoint to exp-dir/ whenever
         params.batch_idx_train % save_every_n == 0. The checkpoint filename