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 +1,154 @@
+# 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.script import ir as I
+from tvm.script import relax as R
+from tvm.script import tirx as T
+
+
+def test_simple():
+    @I.ir_module
+    class Before:
+        @R.function
+        def main():
+            args = Before.func()
+            return args[0]
+
+        @R.function(private=True)
+        def func() -> R.Tuple([R.Tensor, R.Tensor]):
+            A = R.zeros([16, 16], "int32")
+            B = R.ones([16, 16], "int32")
+            return (A, B)
+
+    @I.ir_module
+    class Expected:
+        @R.function
+        def main():
+            A = Expected.func()
+            return A
+
+        @R.function(private=True)
+        def func() -> R.Tensor([16, 16], "int32"):
+            A = R.zeros([16, 16], "int32")
+            return A
+
+    After = tvm.relax.transform.RemoveUnusedOutputs()(Before)
+    tvm.ir.assert_structural_equal(After, Expected)
+
+
+def test_use_multiple_outputs():
+    @I.ir_module
+    class Before:
+        @R.function
+        def main():
+            args = Before.func()
+            return (args[0], args[2])
+
+        @R.function(private=True)
+        def func() -> R.Tuple([R.Tensor, R.Tensor, R.Tensor]):
+            A = R.zeros([16, 16], "int32")
+            B = R.ones([16, 16], "int32")
+            C = R.zeros([32, 32], "int32")
+            return (A, B, C)
+
+    @I.ir_module
+    class Expected:
+        @R.function
+        def main():
+            args = Expected.func()
+            return (args[0], args[1])
+
+        @R.function(private=True)
+        def func() -> R.Tuple([R.Tensor([16, 16], "int32"), R.Tensor([32, 32], "int32")]):
+            A = R.zeros([16, 16], "int32")
+            C = R.zeros([32, 32], "int32")
+            return (A, C)
+
+    After = tvm.relax.transform.RemoveUnusedOutputs()(Before)
+    tvm.ir.assert_structural_equal(After, Expected)
+
+
+def test_multiple_call_sites():
+    @I.ir_module
+    class Before:
+        @R.function
+        def main_a():
+            args = Before.func()
+            return args[0]
+
+        @R.function
+        def main_b():
+            args = Before.func()
+            return args[2]
+
+        @R.function(private=True)
+        def func() -> R.Tuple([R.Tensor, R.Tensor, R.Tensor]):
+            A = R.zeros([16, 16], "int32")
+            B = R.ones([16, 16], "int32")
+            C = R.zeros([32, 32], "int32")
+            return (A, B, C)
+
+    @I.ir_module
+    class Expected:
+        @R.function
+        def main_a():
+            args = Expected.func()
+            return args[0]
+
+        @R.function
+        def main_b():
+            args = Expected.func()
+            return args[1]
+
+        @R.function(private=True)
+        def func() -> R.Tuple([R.Tensor([16, 16], "int32"), R.Tensor([32, 32], "int32")]):
+            A = R.zeros([16, 16], "int32")
+            C = R.zeros([32, 32], "int32")
+            return (A, C)
+
+    After = tvm.relax.transform.RemoveUnusedOutputs()(Before)
+    tvm.ir.assert_structural_equal(After, Expected)
+
+
+def test_return_tuple():
+    @I.ir_module
+    class Before:
+        @R.function
+        def main(A: R.Tensor([16, 16], "int32")):
+            B = R.add(A, A)
+            out_tuple = Before.func(B)
+            return out_tuple
+
+        @R.function(private=True)
+        def func(B: R.Tensor([16, 16], "int32")) -> R.Tuple(
+            R.Tensor([16, 16], "int32"), R.Tensor([16, 16], "int32")
+        ):
+            C = R.multiply(B, B)
+            D = R.add(B, B)
+            return (C, D)
+
+    Expected = Before
+
+    After = tvm.relax.transform.RemoveUnusedOutputs()(Before)
+    tvm.ir.assert_structural_equal(After, Expected)
+
+
+if __name__ == "__main__":
+    tvm.testing.main()