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 +1,106 @@
+# 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 tvm
+import tvm.relax
+import tvm.testing
+from tvm.relax.transform import KillAfterLastUse
+from tvm.script import ir as I
+from tvm.script import relax as R
+
+
+def test_basic():
+    @I.ir_module
+    class Before:
+        @R.function(pure=False)
+        def main(x: R.Tensor([16, 32], "float32")):
+            storage = R.memory.alloc_storage(R.shape([2048]), 0, "global", "uint8")
+            y = R.memory.alloc_tensor(storage, 0, R.shape([16, 32]), "float32")
+            _dummy = R.call_packed("add_tensors", [x, y], ty_args=(R.Tuple,))
+            z = R.add(x, y)
+            return z
+
+    @I.ir_module
+    class Expected:
+        @R.function(pure=False)
+        def main(x: R.Tensor([16, 32], "float32")):
+            storage = R.memory.alloc_storage(R.shape([2048]), 0, "global", "uint8")
+            y = R.memory.alloc_tensor(storage, 0, R.shape([16, 32]), "float32")
+            _ = R.memory.kill_storage(storage)
+            _dummy = R.call_packed("add_tensors", [x, y], ty_args=(R.Tuple,))
+            z = R.add(x, y)
+            _ = R.memory.kill_tensor(y)
+            return z
+
+    After = KillAfterLastUse()(Before)
+    tvm.ir.assert_structural_equal(Expected, After)
+
+
+def test_track_usage_across_trivial_rebindings():
+    """To work around VM de-duplication of register usage"""
+
+    @I.ir_module
+    class Before:
+        @R.function(pure=False)
+        def main(w: R.Tensor([16, 32], "float32")):
+            x = R.add(w, R.const(1, "float32"))
+            y = x
+            z = R.add(y, R.const(1, "float32"))
+            return z
+
+    @I.ir_module
+    class Expected:
+        @R.function(pure=False)
+        def main(w: R.Tensor([16, 32], "float32")):
+            x = R.add(w, R.const(1, "float32"))
+            z = R.add(x, R.const(1, "float32"))
+            _ = R.memory.kill_tensor(x)
+            return z
+
+    After = KillAfterLastUse()(Before)
+    tvm.ir.assert_structural_equal(Expected, After)
+
+
+def test_track_usage_across_trivial_rebindings_in_match_cast():
+    """To work around VM de-duplication of register usage"""
+
+    @I.ir_module
+    class Before:
+        @R.function(pure=False)
+        def main(w: R.Tensor([16, 32], "float32")):
+            x = R.add(w, R.const(1, "float32"))
+            y = R.match_cast(x, R.Tensor([16, 32]))
+            z = R.add(y, R.const(1, "float32"))
+            return z
+
+    @I.ir_module
+    class Expected:
+        @R.function(pure=False)
+        def main(w: R.Tensor([16, 32], "float32")):
+            x = R.add(w, R.const(1, "float32"))
+            y = R.match_cast(x, R.Tensor([16, 32]))
+            _ = R.memory.kill_tensor(x)
+            z = R.add(y, R.const(1, "float32"))
+            _ = R.memory.kill_tensor(y)
+            return z
+
+    After = KillAfterLastUse()(Before)
+    tvm.ir.assert_structural_equal(Expected, After)
+
+
+if __name__ == "__main__":
+    tvm.testing.main()