(self, hidden_size, patch_size, out_channels, cond=False)
| 316 | """ |
| 317 | |
| 318 | def __init__(self, hidden_size, patch_size, out_channels, cond=False): |
| 319 | super().__init__() |
| 320 | self.norm_final = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6) |
| 321 | self.linear = nn.Linear( |
| 322 | hidden_size, patch_size * patch_size * out_channels, bias=True |
| 323 | ) |
| 324 | if cond: |
| 325 | self.adaLN_modulation = nn.Sequential( |
| 326 | nn.SiLU(), nn.Linear(hidden_size, 2 * hidden_size, bias=True) |
| 327 | ) |
| 328 | |
| 329 | def forward(self, x, c=None): |
| 330 | if c is not None: |