Add num_features to train.py for training WSASR (#1528)

egs/librispeech/WSASR/conformer_ctc2/train.py

@@ -31,6 +31,7 @@
  --exp-dir conformer_ctc2/exp \
  --lang-dir data/lang_bpe_200 \
  --otc-token "<star>" \
+ --feature-dim 768 \
  --allow-bypass-arc true \
  --allow-self-loop-arc true \
  --initial-bypass-weight -19 \
@@ -159,6 +160,14 @@ def get_parser():
  "lexicon.txt"
  """,
  )
+
+ parser.add_argument(
+ "--feature-dim",
+ type=int,
+ default=768,
+ help="""Number of features extracted in feature extraction stage.last dimension of feature vector.
+ 80 when using fbank features and 768 or 1024 whn using wave2vec""",
+ )
 
  parser.add_argument(
  "--initial-lr",
@@ -385,7 +394,6 @@ def get_params() -> AttributeDict:
  "valid_interval": 800, # For the 100h subset, use 800
  "alignment_interval": 25,
  # parameters for conformer
- "feature_dim": 768,
  "subsampling_factor": 2,
  "encoder_dim": 512,
  "nhead": 8,