Add conv attention, up and downsampling to vqvae module

1 files changed, 19 insertions, 0 deletions

diff --git a/text_recognizer/networks/vqvae/resize.py b/text_recognizer/networks/vqvae/resize.py
new file mode 100644
index 0000000..769d089
--- /dev/null
+++ b/text_recognizer/networks/vqvae/resize.py
@@ -0,0 +1,19 @@
+"""Up and down-sample with linear interpolation."""
+from torch import nn, Tensor
+import torch.nn.functional as F
+
+
+class Upsample(nn.Module):
+    """Upsamples by a factor 2."""
+
+    def forward(self, x: Tensor) -> Tensor:
+        """Applies upsampling."""
+        return F.interpolate(x, scale_factor=2, mode="nearest")
+
+
+class Downsample(nn.Module):
+    """Downsampling by a factor 2."""
+
+    def forward(self, x: Tensor) -> Tensor:
+        """Applies downsampling."""
+        return F.avg_pool2d(x, kernel_size=2, stride=2)