(self, in_channels, out_channels, modes=16, activation='tanh')
| 222 | |
| 223 | class FourierCrossAttentionW(nn.Module): |
| 224 | def __init__(self, in_channels, out_channels, modes=16, activation='tanh'): |
| 225 | super(FourierCrossAttentionW, self).__init__() |
| 226 | print('corss fourier correlation used!') |
| 227 | self.in_channels = in_channels |
| 228 | self.out_channels = out_channels |
| 229 | self.modes1 = modes |
| 230 | self.activation = activation |
| 231 | |
| 232 | def forward(self, q, k, v, mask): |
| 233 | B, L, E, H = q.shape |