Fix compute_shape_offset non-tuple indexing for PyTorch >=2.9

monai/data/utils.py

@@ -881,7 +881,7 @@ def compute_shape_offset(
             Default is False, using option 1 to compute the shape and offset.
 
     """
-    shape = np.array(spatial_shape, copy=True, dtype=float)
+    shape = np.array(tuple(spatial_shape), copy=True, dtype=float)
     sr = len(shape)
     in_affine_ = convert_data_type(to_affine_nd(sr, in_affine), np.ndarray)[0]
     out_affine_ = convert_data_type(to_affine_nd(sr, out_affine), np.ndarray)[0]

tests/data/utils/test_compute_shape_offset.py

@@ -0,0 +1,34 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+
+import numpy as np
+import torch
+
+from monai.data.utils import compute_shape_offset
+
+
+class TestComputeShapeOffsetRegression(unittest.TestCase):
+    def test_pytorch_size_input(self):
+        # 1 Create a PyTorch Size object (which triggered the original bug)
+        spatial_shape = torch.Size([10, 10, 10])
+        in_affine = np.eye(4)
+        out_affine = np.eye(4)
+
+        # 2 Feed it into the function
+        shape, offset = compute_shape_offset(spatial_shape, in_affine, out_affine)
+
+        # 3 Prove it successfully processed the shape by checking its length
+        self.assertEqual(len(shape), 3)
+
+if __name__ == "__main__":
+    unittest.main()