diff --git a/timm/models/davit.py b/timm/models/davit.py
index 58931cfd..b50e88e3 100644
--- a/timm/models/davit.py
+++ b/timm/models/davit.py
@@ -92,6 +92,7 @@ class PatchEmbed(nn.Module):
                 stride=patch_size,
                 padding=(3, 3))
             self.norm = nn.LayerNorm(embed_dim)
+            self.norm_after = False
         if patch_size[0] == 2:
             kernel = 3 if overlapped else 2
             pad = 1 if overlapped else 0
@@ -102,18 +103,23 @@ class PatchEmbed(nn.Module):
                 stride=patch_size,
                 padding=to_2tuple(pad))
             self.norm = nn.LayerNorm(in_chans)
+            self.norm_after = True
 
 
     def forward(self, x : Tensor, size: Tuple[int, int]):
         H, W = size
-        dim = x.dim()
-        if dim == 3:
-            B, HW, C = x.shape
+        #dim = x.dim()
+        #if dim == 3:
+        in_shape = x.shape
+        B = in_shape[0]
+        C = in_shape[-1]
+        
+        if self.norm_after == False:
             x = self.norm(x)
-            x = x.reshape(B,
-                          H,
-                          W,
-                          C).permute(0, 3, 1, 2).contiguous()
+        x = x.reshape(B,
+                      H,
+                      W,
+                      C).permute(0, 3, 1, 2).contiguous()
 
         B, C, H, W = x.shape
         if W % self.patch_size[1] != 0:
@@ -124,7 +130,8 @@ class PatchEmbed(nn.Module):
         x = self.proj(x)
         newsize = (x.size(2), x.size(3))
         x = x.flatten(2).transpose(1, 2)
-        if dim == 4:
+        #if dim == 4:
+        if self.norm_after == True:
             x = self.norm(x)
         return x, newsize