Update vit_patch_generator.py

vit_patch_generator.py

@@ -116,10 +116,6 @@ class ViTPatchGenerator(nn.Module):
             'pos_embed',
         ]
 
-    def _load_from_state_dict(self, state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs):
-        if self.abs_pos:
-            self._load_embed(state_dict[f'{prefix}pos_embed'], self.pos_embed)
-
     def _load_embed(self, src_embed: torch.Tensor, targ_embed: nn.Parameter):
         if src_embed.shape != targ_embed.shape:
             src_size = int(math.sqrt(src_embed.shape[1]))
@@ -282,18 +278,3 @@ class ViTPatchLinear(nn.Linear):
             **factory
         )
         self.patch_size = patch_size
-
-    def _load_from_state_dict(self, state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs):
-        if self.bias is not None:
-            self.bias.data.copy_(state_dict[f'{prefix}bias'])
-
-        chk_weight = state_dict[f'{prefix}weight']
-        if chk_weight.shape != self.weight.shape:
-            src_patch_size = int(math.sqrt(chk_weight.shape[1] // 3))
-
-            assert (src_patch_size ** 2) * 3 == chk_weight.shape[1], 'Unable to interpolate non-square patch size'
-
-            chk_weight = rearrange(chk_weight, 'b (c h w) -> b c h w', c=3, h=src_patch_size, w=src_patch_size)
-            chk_weight = F.interpolate(chk_weight, size=(self.patch_size, self.patch_size), mode='bicubic', align_corners=True, antialias=False)
-            chk_weight = rearrange(chk_weight, 'b c h w -> b (c h w)')
-        self.weight.data.copy_(chk_weight)