old spaces

timm/models/vision_transformer.py

@@ -166,7 +166,7 @@ class Attention(nn.Module):
     def forward(self, x):
         B, N, C = x.shape
         qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, C // self.num_heads).permute(2, 0, 3, 1, 4)
-        q, k, v = qkv[0], qkv[1], qkv[2]  # make torchscript happy (cannot use tensor as tuple)
+        q, k, v = qkv[0], qkv[1], qkv[2]   # make torchscript happy (cannot use tensor as tuple)
 
         attn = (q @ k.transpose(-2, -1)) * self.scale
         attn = attn.softmax(dim=-1)
@@ -663,7 +663,7 @@ def vit_deit_tiny_distilled_patch16_224(pretrained=False, **kwargs):
     """
     model_kwargs = dict(patch_size=16, embed_dim=192, depth=12, num_heads=3, **kwargs)
     model = _create_vision_transformer(
-        'vit_deit_tiny_distilled_patch16_224', pretrained=pretrained, distilled=True, **model_kwargs)
+        'vit_deit_tiny_distilled_patch16_224', pretrained=pretrained,  distilled=True, **model_kwargs)
     return model
 
 
@@ -674,7 +674,7 @@ def vit_deit_small_distilled_patch16_224(pretrained=False, **kwargs):
     """
     model_kwargs = dict(patch_size=16, embed_dim=384, depth=12, num_heads=6, **kwargs)
     model = _create_vision_transformer(
-        'vit_deit_small_distilled_patch16_224', pretrained=pretrained, distilled=True, **model_kwargs)
+        'vit_deit_small_distilled_patch16_224', pretrained=pretrained,  distilled=True, **model_kwargs)
     return model
 
 
@@ -685,7 +685,7 @@ def vit_deit_base_distilled_patch16_224(pretrained=False, **kwargs):
     """
     model_kwargs = dict(patch_size=16, embed_dim=768, depth=12, num_heads=12, **kwargs)
     model = _create_vision_transformer(
-        'vit_deit_base_distilled_patch16_224', pretrained=pretrained, distilled=True, **model_kwargs)
+        'vit_deit_base_distilled_patch16_224', pretrained=pretrained,  distilled=True, **model_kwargs)
     return model