rename register tables

游雁

2023-12-21 a1b0cd33d50cee3e4612d1e787399e508b453a4a

 funasr/models/transformer/model.py

@@ -15,9 +15,9 @@
from funasr.datasets.audio_datasets.load_audio_extract_fbank import load_audio, extract_fbank
from funasr.utils import postprocess_utils
from funasr.utils.datadir_writer import DatadirWriter
from funasr.utils.register import register_class, registry_tables
from funasr.register import tables

@register_class("model_classes", "Transformer")
@tables.register("model_classes", "Transformer")
class Transformer(nn.Module):
   """CTC-attention hybrid Encoder-Decoder model"""

@@ -60,19 +60,19 @@
      super().__init__()

      if frontend is not None:
         frontend_class = registry_tables.frontend_classes.get_class(frontend.lower())
         frontend_class = tables.frontend_classes.get_class(frontend.lower())
         frontend = frontend_class(**frontend_conf)
      if specaug is not None:
         specaug_class = registry_tables.specaug_classes.get_class(specaug.lower())
         specaug_class = tables.specaug_classes.get_class(specaug.lower())
         specaug = specaug_class(**specaug_conf)
      if normalize is not None:
         normalize_class = registry_tables.normalize_classes.get_class(normalize.lower())
         normalize_class = tables.normalize_classes.get_class(normalize.lower())
         normalize = normalize_class(**normalize_conf)
      encoder_class = registry_tables.encoder_classes.get_class(encoder.lower())
      encoder_class = tables.encoder_classes.get_class(encoder.lower())
      encoder = encoder_class(input_size=input_size, **encoder_conf)
      encoder_output_size = encoder.output_size()
      if decoder is not None:
         decoder_class = registry_tables.decoder_classes.get_class(decoder.lower())
         decoder_class = tables.decoder_classes.get_class(decoder.lower())
         decoder = decoder_class(
            vocab_size=vocab_size,
            encoder_output_size=encoder_output_size,