Remove VQVAE stuff, did not work...

1 files changed, 0 insertions, 54 deletions

diff --git a/text_recognizer/networks/vqvae/residual.py b/text_recognizer/networks/vqvae/residual.py
deleted file mode 100644
index bdff9eb..0000000
--- a/text_recognizer/networks/vqvae/residual.py
+++ /dev/null
@@ -1,54 +0,0 @@
-"""Residual block."""
-import attr
-from torch import nn
-from torch import Tensor
-
-from text_recognizer.networks.util import activation_function
-from text_recognizer.networks.vqvae.norm import Normalize
-
-
-@attr.s(eq=False)
-class Residual(nn.Module):
-    in_channels: int = attr.ib()
-    residual_channels: int = attr.ib()
-    use_norm: bool = attr.ib(default=False)
-    activation: str = attr.ib(default="relu")
-
-    def __attrs_post_init__(self) -> None:
-        """Post init configuration."""
-        super().__init__()
-        self.block = self._build_res_block()
-
-    def _build_res_block(self) -> nn.Sequential:
-        """Build residual block."""
-        block = []
-        activation_fn = activation_function(activation=self.activation)
-
-        if self.use_norm:
-            block.append(Normalize(num_channels=self.in_channels))
-
-        block += [
-            activation_fn,
-            nn.Conv2d(
-                self.in_channels,
-                self.residual_channels,
-                kernel_size=3,
-                padding=1,
-                bias=False,
-            ),
-        ]
-
-        if self.use_norm:
-            block.append(Normalize(num_channels=self.residual_channels))
-
-        block += [
-            activation_fn,
-            nn.Conv2d(
-                self.residual_channels, self.in_channels, kernel_size=1, bias=False
-            ),
-        ]
-        return nn.Sequential(*block)
-
-    def forward(self, x: Tensor) -> Tensor:
-        """Apply the residual forward pass."""
-        return x + self.block(x)