Error on mixed device concatenation (#1156)

anndata/_core/merge.py

@@ -765,6 +765,12 @@ def concat_arrays(arrays, reindexers, axis=0, index=None, fill_value=None):
     elif any(isinstance(a, CupySparseMatrix) for a in arrays):
         import cupyx.scipy.sparse as cpsparse
 
+        if not all(
+            isinstance(a, (CupySparseMatrix, CupyArray)) or 0 in a.shape for a in arrays
+        ):
+            raise NotImplementedError(
+                "Cannot concatenate a cupy array with other array types."
+            )
         sparse_stack = (cpsparse.vstack, cpsparse.hstack)[axis]
         return sparse_stack(
             [

anndata/tests/test_concatenate.py

@@ -4,7 +4,7 @@
 from collections.abc import Hashable
 from copy import deepcopy
 from functools import partial, singledispatch
-from itertools import chain, product
+from itertools import chain, permutations, product
 from typing import Any, Callable
 
 import numpy as np
@@ -1454,3 +1454,44 @@ def test_concat_duplicated_columns(join_type):
 
     with pytest.raises(pd.errors.InvalidIndexError, match=r"'a'"):
         concat([a, b], join=join_type)
+
+
+@pytest.mark.gpu
+def test_error_on_mixed_device():
+    """https://github.com/scverse/anndata/issues/1083"""
+    import cupy
+    import cupyx.scipy.sparse as cupy_sparse
+
+    cp_adata = AnnData(
+        cupy.random.randn(10, 10),
+        obs=pd.DataFrame(index=[f"cell_{i:02d}" for i in range(10)]),
+    )
+    cp_sparse_adata = AnnData(
+        cupy_sparse.random(10, 10, format="csr", density=0.2),
+        obs=pd.DataFrame(index=[f"cell_{i:02d}" for i in range(10, 20)]),
+    )
+    np_adata = AnnData(
+        np.random.randn(10, 10),
+        obs=pd.DataFrame(index=[f"cell_{i:02d}" for i in range(20, 30)]),
+    )
+    sparse_adata = AnnData(
+        sparse.random(10, 10, format="csr", density=0.2),
+        obs=pd.DataFrame(index=[f"cell_{i:02d}" for i in range(30, 40)]),
+    )
+
+    adatas = {
+        "cupy": cp_adata,
+        "cupy_sparse": cp_sparse_adata,
+        "numpy": np_adata,
+        "sparse": sparse_adata,
+    }
+
+    for p in map(dict, permutations(adatas.items())):
+        print(list(p.keys()))
+        with pytest.raises(
+            NotImplementedError, match="Cannot concatenate a cupy array with other"
+        ):
+            concat(p)
+
+    for p in permutations([cp_adata, cp_sparse_adata]):
+        concat(p)