chore: import upstream snapshot with attribution

tests/python/runtime/test_runtime_extension.py

@@ -0,0 +1,42 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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 numpy as np
+
+import tvm
+from tvm.script import ir as I
+from tvm.script import tirx as T
+
+
+def test_dltensor_compatible():
+    @I.ir_module
+    class Module:
+        @T.prim_func(s_tir=True)
+        def arange(A: T.handle):
+            n = T.int32()
+            Ab = T.match_buffer(A, (n,), "int64")
+            for i in T.serial(n - 1):
+                Ab[i + 1] = Ab[i] + T.int64(1)
+
+    mod = Module
+    f = tvm.compile(mod, target="llvm")
+    a = tvm.runtime.tensor(np.zeros(10, dtype="int64"))
+    f(a)
+    np.testing.assert_equal(a.numpy(), np.arange(a.shape[0]))
+
+
+if __name__ == "__main__":
+    test_dltensor_compatible()