diff options
| author | Jordan Gong <jordan.gong@protonmail.com> | 2021-02-08 18:11:25 +0800 |
|---|---|---|
| committer | Jordan Gong <jordan.gong@protonmail.com> | 2021-02-08 18:25:42 +0800 |
| commit | 99ddd7c142a4ec97cb8bd14b204651790b3cf4ee (patch) | |
| tree | a4ccbd08a7155e90df63aba60eb93ab2b7969c9b /models/layers.py | |
| parent | 507e1d163aaa6ea4be23e7f08ff6ce0ef58c830b (diff) | |
Code refactoring, modifications and new features
1. Decode features outside of auto-encoder
2. Turn off HPM 1x1 conv by default
3. Change canonical feature map size from `feature_channels * 8 x 4 x 2` to `feature_channels * 2 x 16 x 8`
4. Use mean of canonical embeddings instead of mean of static features
5. Calculate static and dynamic loss separately
6. Calculate mean of parts in triplet loss instead of sum of parts
7. Add switch to log disentangled images
8. Change default configuration
Diffstat (limited to 'models/layers.py')
| -rw-r--r-- | models/layers.py | 10 |
1 files changed, 6 insertions, 4 deletions
diff --git a/models/layers.py b/models/layers.py index a9f04b3..7b6ba5c 100644 --- a/models/layers.py +++ b/models/layers.py @@ -167,12 +167,13 @@ class HorizontalPyramidPooling(BasicConv2d): self, in_channels: int, out_channels: int, - kernel_size: Union[int, tuple[int, int]] = 1, + use_1x1conv: bool = False, use_avg_pool: bool = True, - use_max_pool: bool = True, + use_max_pool: bool = False, **kwargs ): - super().__init__(in_channels, out_channels, kernel_size, **kwargs) + super().__init__(in_channels, out_channels, kernel_size=1, **kwargs) + self.use_1x1conv = use_1x1conv self.use_avg_pool = use_avg_pool self.use_max_pool = use_max_pool assert use_avg_pool or use_max_pool, 'Pooling layer(s) required.' @@ -186,5 +187,6 @@ class HorizontalPyramidPooling(BasicConv2d): x = self.avg_pool(x) elif not self.use_avg_pool and self.use_max_pool: x = self.max_pool(x) - x = super().forward(x) + if self.use_1x1conv: + x = super().forward(x) return x |