(self)
| 32 | |
| 33 | # 定义权值初始化 |
| 34 | def initialize_weights(self): |
| 35 | for m in self.modules(): |
| 36 | if isinstance(m, nn.Conv2d): |
| 37 | torch.nn.init.xavier_normal_(m.weight.data) |
| 38 | if m.bias is not None: |
| 39 | m.bias.data.zero_() |
| 40 | elif isinstance(m, nn.BatchNorm2d): |
| 41 | m.weight.data.fill_(1) |
| 42 | m.bias.data.zero_() |
| 43 | elif isinstance(m, nn.Linear): |
| 44 | torch.nn.init.normal_(m.weight.data, 0, 0.01) |
| 45 | m.bias.data.zero_() |
| 46 | |
| 47 | class MyDataset(Dataset): |
| 48 | def __init__(self, txt_path, transform = None, target_transform = None): |
nothing calls this directly
no outgoing calls
no test coverage detected