diff options
Diffstat (limited to 'models')
| -rw-r--r-- | models/convnext/discriminator.py | 8 | ||||
| -rw-r--r-- | models/sparse.py | 2 |
2 files changed, 2 insertions, 8 deletions
diff --git a/models/convnext/discriminator.py b/models/convnext/discriminator.py index 7dbbe3a..571b915 100644 --- a/models/convnext/discriminator.py +++ b/models/convnext/discriminator.py | |||
| @@ -15,13 +15,7 @@ class ConvNeXtDiscriminator(): | |||
| 15 | self.img_std = torch.tensor(IMAGENET_DEFAULT_STD).view(1, -1, 1, 1) | 15 | self.img_std = torch.tensor(IMAGENET_DEFAULT_STD).view(1, -1, 1, 1) |
| 16 | 16 | ||
| 17 | def get_score(self, img): | 17 | def get_score(self, img): |
| 18 | img_mean = self.img_mean.to(device=img.device, dtype=img.dtype) | 18 | pred = self.get_all(img) |
| 19 | img_std = self.img_std.to(device=img.device, dtype=img.dtype) | ||
| 20 | |||
| 21 | img = ((img+1.)/2.).sub(img_mean).div(img_std) | ||
| 22 | |||
| 23 | img = F.interpolate(img, size=(self.input_size, self.input_size), mode='bicubic', align_corners=True) | ||
| 24 | pred = self.net(img) | ||
| 25 | return torch.softmax(pred, dim=-1)[:, 1] | 19 | return torch.softmax(pred, dim=-1)[:, 1] |
| 26 | 20 | ||
| 27 | def get_all(self, img): | 21 | def get_all(self, img): |
diff --git a/models/sparse.py b/models/sparse.py index bcb2897..07b3413 100644 --- a/models/sparse.py +++ b/models/sparse.py | |||
| @@ -15,7 +15,7 @@ class PseudoSparseEmbedding(nn.Module): | |||
| 15 | if dropout_p > 0.0: | 15 | if dropout_p > 0.0: |
| 16 | self.dropout = nn.Dropout(p=dropout_p) | 16 | self.dropout = nn.Dropout(p=dropout_p) |
| 17 | else: | 17 | else: |
| 18 | self.dropout = lambda x: x | 18 | self.dropout = nn.Identity() |
| 19 | 19 | ||
| 20 | self.register_buffer('mapping', torch.zeros(0, device=device, dtype=torch.long)) | 20 | self.register_buffer('mapping', torch.zeros(0, device=device, dtype=torch.long)) |
| 21 | 21 | ||