address https://github.com/lucidrains/vit-pytorch/issues/266

.github/workflows/python-test.yml

@@ -27,6 +27,7 @@ jobs:
       run: |
         python -m pip install --upgrade pip
         python -m pip install pytest
+        python -m pip install wheel
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
     - name: Test with pytest
       run: |

setup.py

@@ -3,7 +3,7 @@ from setuptools import setup, find_packages
 setup(
   name = 'vit-pytorch',
   packages = find_packages(exclude=['examples']),
-  version = '1.2.0',
+  version = '1.2.2',
   license='MIT',
   description = 'Vision Transformer (ViT) - Pytorch',
   long_description_content_type = 'text/markdown',
@@ -16,7 +16,7 @@ setup(
     'image recognition'
   ],
   install_requires=[
-    'einops>=0.6.0',
+    'einops>=0.6.1',
     'torch>=1.10',
     'torchvision'
   ],

vit_pytorch/__init__.py

@@ -1,3 +1,10 @@
+import torch
+from packaging import version
+
+if version.parse(torch.__version__) >= version.parse('2.0.0'):
+    from einops._torch_specific import allow_ops_in_compiled_graph
+    allow_ops_in_compiled_graph()
+
 from vit_pytorch.vit import ViT
 from vit_pytorch.simple_vit import SimpleViT
 

vit_pytorch/vivit.py

@@ -146,7 +146,7 @@ class ViT(nn.Module):
         x = self.to_patch_embedding(video)
         b, f, n, _ = x.shape
 
-        x = x + self.pos_embedding
+        x = x + self.pos_embedding[:, :f, :n]
 
         if exists(self.spatial_cls_token):
             spatial_cls_tokens = repeat(self.spatial_cls_token, '1 1 d -> b f 1 d', b = b, f = f)