Update davit.py

timm/models/davit.py

@@ -68,61 +68,6 @@ class ConvPosEnc(nn.Module):
         return x
 
 
-@register_notrace_module
-class PatchEmbedOld(nn.Module):
-    """ Size-agnostic implementation of 2D image to patch embedding,
-        allowing input size to be adjusted during model forward operation
-    """
-
-    def __init__(
-            self,
-            patch_size=4,
-            in_chans=3,
-            embed_dim=96,
-            overlapped=False):
-        super().__init__()
-        patch_size = to_2tuple(patch_size)
-        self.patch_size = patch_size
-        self.in_chans = in_chans
-        self.embed_dim = embed_dim
-
-        if patch_size[0] == 4:
-            self.proj = nn.Conv2d(
-                in_chans,
-                embed_dim,
-                kernel_size=(7, 7),
-                stride=patch_size,
-                padding=(3, 3))
-            self.norm = nn.LayerNorm(embed_dim)
-        if patch_size[0] == 2:
-            kernel = 3 if overlapped else 2
-            pad = 1 if overlapped else 0
-            self.proj = nn.Conv2d(
-                in_chans,
-                embed_dim,
-                kernel_size=to_2tuple(kernel),
-                stride=patch_size,
-                padding=to_2tuple(pad))
-            self.norm = nn.LayerNorm(in_chans)
-
-    
-    def forward(self, x : Tensor):
-        B, C, H, W = x.shape
-        if self.norm.normalized_shape[0] == self.in_chans:
-            x = self.norm(x.permute(0, 2, 3, 1)).permute(0, 3, 1, 2)
-
-        if W % self.patch_size[1] != 0:
-            x = F.pad(x, (0, self.patch_size[1] - W % self.patch_size[1]))
-        if H % self.patch_size[0] != 0:
-            x = F.pad(x, (0, 0, 0, self.patch_size[0] - H % self.patch_size[0]))
-
-        x = self.proj(x)
-
-        if self.norm.normalized_shape[0] == self.embed_dim:
-            x = self.norm(x.permute(0, 2, 3, 1)).permute(0, 3, 1, 2)
-        return x
-
-
 class PatchEmbed(nn.Module):
     """ Size-agnostic implementation of 2D image to patch embedding,
         allowing input size to be adjusted during model forward operation