| 313 | self.is_bn_merged = True |
| 314 | |
| 315 | def forward(self, x): |
| 316 | x = self.patch_embed(x) |
| 317 | B, C, H, W = x.shape |
| 318 | if not torch.onnx.is_in_onnx_export() and not self.is_bn_merged: |
| 319 | out = self.norm1(x) |
| 320 | else: |
| 321 | out = x |
| 322 | out = rearrange(out, "b c h w -> b (h w) c") # b n c |
| 323 | out = self.mhsa_path_dropout(self.e_mhsa(out)) |
| 324 | x = x + rearrange(out, "b (h w) c -> b c h w", h=H) |
| 325 | |
| 326 | out = self.projection(x) |
| 327 | out = out + self.mhca_path_dropout(self.mhca(out)) |
| 328 | x = torch.cat([x, out], dim=1) |
| 329 | |
| 330 | if not torch.onnx.is_in_onnx_export() and not self.is_bn_merged: |
| 331 | out = self.norm2(x) |
| 332 | else: |
| 333 | out = x |
| 334 | x = x + self.mlp_path_dropout(self.mlp(out)) |
| 335 | return x |
| 336 | |
| 337 | |
| 338 | class NextViT(nn.Module): |