コード例 #1
0
ファイル: waveglow.py プロジェクト: wgfi110/NeMo
 def remove_weightnorm(self):
     for wavenet in self.wavenet:
         wavenet.start = torch.nn.utils.remove_weight_norm(wavenet.start)
         wavenet.in_layers = remove(wavenet.in_layers)
         wavenet.cond_layer = torch.nn.utils.remove_weight_norm(
             wavenet.cond_layer)
         wavenet.res_skip_layers = remove(wavenet.res_skip_layers)
コード例 #2
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def remove_weightnorm(model):
    squeezewave = model
    for wavenet in squeezewave.wavenet:
        wavenet.start = torch.nn.utils.remove_weight_norm(wavenet.start)
        wavenet.in_layers = remove_batchnorm(wavenet.in_layers)
        wavenet.cond_layer = torch.nn.utils.remove_weight_norm(
            wavenet.cond_layer)
        wavenet.res_skip_layers = remove(wavenet.res_skip_layers)
    return squeezewave
コード例 #3
0
ファイル: uniglow.py プロジェクト: quuhua911/NeMo
 def remove_weightnorm(self):
     self.wn.start = torch.nn.utils.remove_weight_norm(self.wn.start)
     self.wn.in_layers = remove(self.wn.in_layers)
     self.wn.cond_layer = torch.nn.utils.remove_weight_norm(
         self.wn.cond_layer)
     self.wn.res_skip_layers = remove(self.wn.res_skip_layers)