Better timm compatibility fix

Author: semjonsona

dmidas/backbones/beit.py

@@ -95,13 +95,15 @@ def block_forward(self, x, resolution, shared_rel_pos_bias: Optional[torch.Tenso
     """
     Modification of timm.models.beit.py: Block.forward to support arbitrary window sizes.
     """
+    if hasattr(self, 'drop_path1') and not hasattr(self, 'drop_path'):
+        self.drop_path = self.drop_path1
     if self.gamma_1 is None:
-        x = x + self.drop_path1(self.attn(self.norm1(x), resolution, shared_rel_pos_bias=shared_rel_pos_bias))
-        x = x + self.drop_path2(self.mlp(self.norm2(x)))
+        x = x + self.drop_path(self.attn(self.norm1(x), resolution, shared_rel_pos_bias=shared_rel_pos_bias))
+        x = x + self.drop_path(self.mlp(self.norm2(x)))
     else:
-        x = x + self.drop_path1(self.gamma_1 * self.attn(self.norm1(x), resolution,
+        x = x + self.drop_path(self.gamma_1 * self.attn(self.norm1(x), resolution,
                                                         shared_rel_pos_bias=shared_rel_pos_bias))
-        x = x + self.drop_path2(self.gamma_2 * self.mlp(self.norm2(x)))
+        x = x + self.drop_path(self.gamma_2 * self.mlp(self.norm2(x)))
     return x
 
 

dzoedepth/models/base_models/midas.py

@@ -340,7 +340,7 @@ def build(midas_model_type="DPT_BEiT_L_384", train_midas=False, use_pretrained_m
         print("img_size", img_size)
         # TODO: use locally-bundled midas
         # The repo should be changed back to isl-org/MiDaS once this MR lands
-        midas = torch.hub.load("AyaanShah2204/MiDaS", midas_model_type,
+        midas = torch.hub.load("semjon00/MiDaS", midas_model_type,
                                pretrained=use_pretrained_midas, force_reload=force_reload)
         kwargs.update({'keep_aspect_ratio': force_keep_ar})
         midas_core = MidasCore(midas, trainable=train_midas, fetch_features=fetch_features,