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wrap checking for metadata when adding a voice in case it throws an error

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mrq 2023-02-21 17:35:30 +00:00
parent b6f7aa6264
commit ed2cf9f5ee
1 changed files with 24 additions and 10 deletions
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34
src/utils.py
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@ -490,6 +490,17 @@ def stop_training():
training_process.kill()
return "Training cancelled"
def convert_to_halfp():
autoregressive_model_path = get_model_path('autoregressive.pth')
model = torch.load(autoregressive_model_path)
for k in model:
if re.findall(r'\.weight$', k):
print(f"Converting: {k}")
model[k] = model[k].half()
torch.save(model, './models/tortoise/autoregressive_half.pth')
print('Converted model to half precision: ./models/tortoise/autoregressive_half.pth')
def prepare_dataset( files, outdir, language=None, progress=None ):
unload_tts()
@ -961,17 +972,20 @@ def read_generate_settings(file, read_latents=True):
if isinstance(file, list) and len(file) == 1:
file = file[0]
if file is not None:
if hasattr(file, 'name'):
file = file.name
try:
if file is not None:
if hasattr(file, 'name'):
file = file.name
if file[-4:] == ".wav":
metadata = music_tag.load_file(file)
if 'lyrics' in metadata:
j = json.loads(str(metadata['lyrics']))
elif file[-5:] == ".json":
with open(file, 'r') as f:
j = json.load(f)
if file[-4:] == ".wav":
metadata = music_tag.load_file(file)
if 'lyrics' in metadata:
j = json.loads(str(metadata['lyrics']))
elif file[-5:] == ".json":
with open(file, 'r') as f:
j = json.load(f)
except Exception as e:
pass
if j is None:
print("No metadata found in audio file to read")