| 130 | return outputBatch |
| 131 | |
| 132 | class DSConv1d(nn.Module): |
| 133 | def __init__(self): |
| 134 | super(DSConv1d, self).__init__() |
| 135 | self.net = nn.Sequential( |
| 136 | nn.ReLU(), |
| 137 | nn.BatchNorm1d(512), |
| 138 | nn.Conv1d(512, 512, 3, stride=1, padding=1,dilation=1, groups=512, bias=False), |
| 139 | nn.PReLU(), |
| 140 | GlobalLayerNorm(512), |
| 141 | nn.Conv1d(512, 512, 1, bias=False), |
| 142 | ) |
| 143 | |
| 144 | def forward(self, x): |
| 145 | out = self.net(x) |
| 146 | return out + x |
| 147 | |
| 148 | class visualTCN(nn.Module): |
| 149 | def __init__(self): |