(self, lr = 0.0001, lrDecay = 0.95, **kwargs)
| 9 | |
| 10 | class talkNet(nn.Module): |
| 11 | def __init__(self, lr = 0.0001, lrDecay = 0.95, **kwargs): |
| 12 | super(talkNet, self).__init__() |
| 13 | self.model = talkNetModel().cuda() |
| 14 | self.lossAV = lossAV().cuda() |
| 15 | self.lossA = lossA().cuda() |
| 16 | self.lossV = lossV().cuda() |
| 17 | self.optim = torch.optim.Adam(self.parameters(), lr = lr) |
| 18 | self.scheduler = torch.optim.lr_scheduler.StepLR(self.optim, step_size = 1, gamma=lrDecay) |
| 19 | print(time.strftime("%m-%d %H:%M:%S") + " Model para number = %.2f"%(sum(param.numel() for param in self.model.parameters()) / 1024 / 1024)) |
| 20 | |
| 21 | def train_network(self, loader, epoch, **kwargs): |
| 22 | self.train() |
nothing calls this directly
no test coverage detected