def train(_):
if config.mode == "sep":
if config.use_content:
model = models.SSSynth_Content()
else:
model = models.SSSynth()
elif config.mode == "mask":
model = models.MaskSep()
elif config.mode == "chain":
model = models.Chain()
model.train()
def eval_wav_folder(folder_name):
if config.mode == "sep":
if config.use_content:
model = models.SSSynth_Content()
else:
model = models.SSSynth()
elif config.mode == "mask":
model = models.MaskSep()
model.test_folder_wav(folder_name)
def eval_wav_file(file_name, acap_file=None):
if config.mode == "sep":
if config.use_content:
model = models.SSSynth_Content()
else:
model = models.SSSynth()
elif config.mode == "mask":
model = models.MaskSep()
elif config.mode == "chain":
model = models.Chain()
model.test_file_wav(file_name, acap_file)
def eval_hdf5_file(file_name, speaker_alt=None):
if config.mode == "voc" or config.mode == "ori":
model = models.AutoVC()
elif config.mode == "stft_voc":
model = models.AutoVCSTFT()
if config.mode == "voc" or config.mode == "ori" or config.mode == "stft_voc":
speaker_name = file_name.split('_')[1]
speaker_index = config.singers.index(speaker_name)
if not speaker_alt:
model.test_file_hdf5(file_name, speaker_index, speaker_index)
else:
model.test_file_hdf5(file_name, speaker_index, speaker_alt)
elif config.mode == "sep":
if config.use_content:
model = models.SSSynth_Content()
model.test_file_hdf5(file_name)
else:
model = models.SSSynth()
model.test_file_hdf5(file_name)
elif config.mode == "npss":
model = models.NPSS()
model.test_file_hdf5(file_name)
def train(_):
model = models.SSSynth()
model.train()
def eval_hdf5_file(file_name):
model = models.SSSynth()
model.test_file_hdf5(file_name)
def test(_):
model = models.SSSynth()
model.test_model_yam()