Traceability fix for vit models for some experiments

timm/models/layers/patch_embed.py

@@ -6,7 +6,7 @@ Based on the impl in https://github.com/google-research/vision_transformer
 
 Hacked together by / Copyright 2020 Ross Wightman
 """
-
+import torch
 from torch import nn as nn
 
 from .helpers import to_2tuple
@@ -30,8 +30,8 @@ class PatchEmbed(nn.Module):
 
     def forward(self, x):
         B, C, H, W = x.shape
-        assert H == self.img_size[0] and W == self.img_size[1], \
+        torch._assert(H == self.img_size[0], f"Input image height ({H}) doesn't match model {self.img_size[0]}.")
-            f"Input image size ({H}*{W}) doesn't match model ({self.img_size[0]}*{self.img_size[1]})."
+        torch._assert(W == self.img_size[1], f"Input image width ({W}) doesn't match model ({self.img_size[1]}.")
         x = self.proj(x)
         if self.flatten:
             x = x.flatten(2).transpose(1, 2)  # BCHW -> BNC