Medix-AI/coqui-tts
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coqui-tts
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load model checkpoint on cpu, set 'r' for all models with gradual training enabled for all

This commit is contained in:
Eren Golge 2019-12-10 11:21:55 +01:00 committed by Reuben Morais
parent ca49ae8b5e
commit e2e92b63d5
1 changed files with 2 additions and 3 deletions
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5
server/synthesizer.py
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@ -53,15 +53,14 @@ class Synthesizer(object):
num_speakers = 0 num_speakers = 0
self.tts_model = setup_model(self.input_size, num_speakers=num_speakers, c=self.tts_config) self.tts_model = setup_model(self.input_size, num_speakers=num_speakers, c=self.tts_config)
# load model state # load model state
map_location = None if use_cuda else torch.device('cpu') cp = torch.load(tts_checkpoint, map_location=torch.device('cpu'))
cp = torch.load(tts_checkpoint, map_location=map_location)
# load the model # load the model
self.tts_model.load_state_dict(cp['model']) self.tts_model.load_state_dict(cp['model'])
if use_cuda: if use_cuda:
self.tts_model.cuda() self.tts_model.cuda()
self.tts_model.eval() self.tts_model.eval()
self.tts_model.decoder.max_decoder_steps = 3000 self.tts_model.decoder.max_decoder_steps = 3000
if 'r' in cp and self.tts_config.model in ["Tacotron", "TacotronGST"]: if 'r' in cp:
self.tts_model.decoder.set_r(cp['r']) self.tts_model.decoder.set_r(cp['r'])
def load_wavernn(self, lib_path, model_path, model_file, model_config, use_cuda): def load_wavernn(self, lib_path, model_path, model_file, model_config, use_cuda):