HoneyTian commited on
Commit
3e60665
β€’
1 Parent(s): 2fb8b3a
.gitattributes CHANGED
@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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  *.wav filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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  *.wav filter=lfs diff=lfs merge=lfs -text
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+ *.whl filter=lfs diff=lfs merge=lfs -text
examples/wenet/toolbox_infer.py CHANGED
@@ -18,7 +18,7 @@ import torchaudio
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  from project_settings import project_path, temp_directory
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  from toolbox.k2_sherpa.utils import audio_convert
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- from toolbox.k2_sherpa import decode, models
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  def get_args():
@@ -51,13 +51,13 @@ def main():
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  )
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  # load recognizer
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- m_dict = models.model_map["Chinese"][0]
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  local_model_dir = Path(args.model_dir)
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  nn_model_file = local_model_dir / m_dict["nn_model_file"]
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  tokens_file = local_model_dir / m_dict["tokens_file"]
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- recognizer = models.load_recognizer(
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  repo_id=m_dict["repo_id"],
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  nn_model_file=nn_model_file.as_posix(),
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  tokens_file=tokens_file.as_posix(),
 
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  from project_settings import project_path, temp_directory
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  from toolbox.k2_sherpa.utils import audio_convert
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+ from toolbox.k2_sherpa import decode, nn_models
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  def get_args():
 
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  )
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  # load recognizer
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+ m_dict = nn_models.model_map["Chinese"][0]
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  local_model_dir = Path(args.model_dir)
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  nn_model_file = local_model_dir / m_dict["nn_model_file"]
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  tokens_file = local_model_dir / m_dict["tokens_file"]
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+ recognizer = nn_models.load_recognizer(
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  repo_id=m_dict["repo_id"],
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  nn_model_file=nn_model_file.as_posix(),
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  tokens_file=tokens_file.as_posix(),
main.py CHANGED
@@ -21,7 +21,7 @@ import torch
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  import torchaudio
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  from toolbox.k2_sherpa.examples import examples
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- from toolbox.k2_sherpa import decode, models
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  from toolbox.k2_sherpa.utils import audio_convert
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  main_logger = logging.getLogger("main")
@@ -40,10 +40,10 @@ def get_args():
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  def update_model_dropdown(language: str):
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- if language not in models.model_map.keys():
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  raise ValueError(f"Unsupported language: {language}")
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- choices = models.model_map[language]
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  choices = [c["repo_id"] for c in choices]
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  return gr.Dropdown(
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  choices=choices,
@@ -88,7 +88,7 @@ def process(
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  )
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  # model settings
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- m_list = models.model_map.get(language)
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  if m_list is None:
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  raise AssertionError("language invalid: {}".format(language))
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@@ -104,7 +104,7 @@ def process(
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  nn_model_file = local_model_dir / m_dict["nn_model_file"]
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  tokens_file = local_model_dir / m_dict["tokens_file"]
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- recognizer = models.load_recognizer(
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  repo_id=m_dict["repo_id"],
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  nn_model_file=nn_model_file.as_posix(),
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  tokens_file=tokens_file.as_posix(),
@@ -202,10 +202,10 @@ def main():
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  title = "# Automatic Speech Recognition with Next-gen Kaldi"
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- language_choices = list(models.model_map.keys())
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  language_to_models = defaultdict(list)
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- for k, v in models.model_map.items():
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  for m in v:
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  repo_id = m["repo_id"]
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  language_to_models[k].append(repo_id)
 
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  import torchaudio
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  from toolbox.k2_sherpa.examples import examples
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+ from toolbox.k2_sherpa import decode, nn_models
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  from toolbox.k2_sherpa.utils import audio_convert
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  main_logger = logging.getLogger("main")
 
40
 
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  def update_model_dropdown(language: str):
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+ if language not in nn_models.model_map.keys():
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  raise ValueError(f"Unsupported language: {language}")
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+ choices = nn_models.model_map[language]
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  choices = [c["repo_id"] for c in choices]
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  return gr.Dropdown(
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  choices=choices,
 
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  )
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  # model settings
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+ m_list = nn_models.model_map.get(language)
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  if m_list is None:
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  raise AssertionError("language invalid: {}".format(language))
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  nn_model_file = local_model_dir / m_dict["nn_model_file"]
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  tokens_file = local_model_dir / m_dict["tokens_file"]
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+ recognizer = nn_models.load_recognizer(
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  repo_id=m_dict["repo_id"],
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  nn_model_file=nn_model_file.as_posix(),
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  tokens_file=tokens_file.as_posix(),
 
202
 
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  title = "# Automatic Speech Recognition with Next-gen Kaldi"
204
 
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+ language_choices = list(nn_models.model_map.keys())
206
 
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  language_to_models = defaultdict(list)
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+ for k, v in nn_models.model_map.items():
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  for m in v:
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  repo_id = m["repo_id"]
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  language_to_models[k].append(repo_id)
toolbox/k2_sherpa/{models.py β†’ nn_models.py} RENAMED
File without changes