chore: import upstream snapshot with attribution

2026-07-13 13:36:25 +08:00
commit 26446540fa
3151 changed files with 974126 additions and 0 deletions
@@ -0,0 +1,131 @@
+# 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.
+# ruff: noqa: F401
+
+import tvm
+import tvm.testing
+from tvm.ir import VDevice
+from tvm.relax.transform import UpdateVDevice
+from tvm.script.parser import ir as I
+from tvm.script.parser import relax as R
+from tvm.script.parser import tirx as T
+
+
+def verify(input, new_vdevice, vdevice_index, expected):
+    tvm.ir.assert_structural_equal(UpdateVDevice(new_vdevice, vdevice_index)(input), expected)
+
+
+def test_update():
+    vdevices = [
+        VDevice("llvm"),
+        VDevice("cuda", 0),
+        VDevice("metal", 0, "global"),
+        VDevice({"kind": "cuda", "arch": "sm_80"}, 0),
+        VDevice("metal", 1, "global"),
+        VDevice("llvm", 1),
+    ]
+
+    @I.ir_module
+    class Input1:
+        I.module_attrs({"attr": 10})
+        I.module_global_infos(
+            {
+                "vdevice": [
+                    I.vdevice("llvm"),
+                    I.vdevice("cuda", 0),
+                    I.vdevice("metal", 0, "global"),
+                    I.vdevice({"kind": "cuda", "arch": "sm_80"}, 0),
+                ]
+            }
+        )
+
+        @R.function
+        def main(
+            a: R.Tensor((128, 128), "float32", "cuda:1"),
+            c: R.Tensor((128, 128), "float32", "vdevice:3"),
+        ) -> R.Tensor((128, 128), "float32"):
+            s = R.add(a, c)
+            return s
+
+    @I.ir_module
+    class Expect1:
+        I.module_attrs({"attr": 10})
+        I.module_global_infos(
+            {
+                "vdevice": [
+                    I.vdevice("llvm"),
+                    I.vdevice("cuda", 0),
+                    I.vdevice("metal", 0, "global"),
+                    I.vdevice("metal", 1, "global"),
+                ]
+            }
+        )
+
+        @R.function
+        def main(
+            a: R.Tensor((128, 128), dtype="float32", vdevice="metal:1"),
+            c: R.Tensor((128, 128), dtype="float32", vdevice="metal:1"),
+        ) -> R.Tensor((128, 128), dtype="float32", vdevice="metal:1"):
+            s: R.Tensor((128, 128), dtype="float32", vdevice="metal:1") = R.add(a, c)
+            return s
+
+    @I.ir_module
+    class Input2:
+        I.module_attrs({"attr": 10})
+        I.module_global_infos(
+            {
+                "vdevice": [
+                    I.vdevice("llvm"),
+                    I.vdevice("cuda", 0),
+                ]
+            }
+        )
+
+        @R.function
+        def main(
+            a: R.Tensor((128, 128), "float32", "cuda:0"),
+            c: R.Tensor((128, 128), "float32", "cuda:0"),
+        ) -> R.Tensor((128, 128), "float32"):
+            s = R.add(a, c)
+            return s
+
+    @I.ir_module
+    class Expect2:
+        I.module_attrs({"attr": 10})
+        I.module_global_infos(
+            {
+                "vdevice": [
+                    I.vdevice("llvm"),
+                    I.vdevice("llvm", 1),
+                ]
+            }
+        )
+
+        @R.function
+        def main(
+            a: R.Tensor((128, 128), "float32", "llvm:1"),
+            c: R.Tensor((128, 128), "float32", "llvm:1"),
+        ) -> R.Tensor((128, 128), "float32", "llvm:1"):
+            s: R.Tensor((128, 128), "float32", "llvm:1") = R.add(a, c)
+            return s
+
+    verify(Input1, vdevices[4], 3, Expect1)
+    verify(Input2, vdevices[5], 1, Expect2)
+
+
+if __name__ == "__main__":
+    tvm.testing.main()