def init_params(self):
for param in self.parameters():
if param.requires_grad:
if cfg.use_truncated_normal:
truncated_normal_(param, std=0.1)
else:
torch.nn.init.normal_(param, std=0.1)
def init_params(self):
for param in self.parameters():
if param.requires_grad and len(param.shape) > 0:
stddev = 1 / math.sqrt(param.shape[0])
if cfg.use_truncated_normal:
truncated_normal_(param, std=stddev)
else:
torch.nn.init.normal_(param, std=stddev)
def init_params(self):
for param in self.parameters():
if param.requires_grad and len(param.shape) > 0:
stddev = 1 / math.sqrt(param.shape[0])
if cfg.dis_init == 'uniform':
torch.nn.init.uniform_(param, a=-0.05, b=0.05)
elif cfg.dis_init == 'normal':
torch.nn.init.normal_(param, std=stddev)
elif cfg.dis_init == 'truncated_normal':
truncated_normal_(param, std=stddev)
