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 +1,63 @@
+# 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
+"""LLVM enablement tests."""
+
+import ctypes
+import math
+import re
+
+import numpy as np
+import pytest
+
+import tvm
+import tvm.testing
+from tvm import te, topi
+from tvm.support import utils
+from tvm.testing import env
+
+
+@pytest.mark.skipif(not env.has_llvm(), reason="need llvm")
+def test_llvm_add_pipeline():
+    """all-platform-minimal-test: Check LLVM enablement."""
+    nn = 128
+    n = tvm.runtime.convert(nn)
+    A = te.placeholder((n,), name="A")
+    B = te.placeholder((n,), name="B")
+    AA = te.compute((n,), lambda *i: A(*i), name="A")
+    BB = te.compute((n,), lambda *i: B(*i), name="B")
+    T = te.compute(A.shape, lambda *i: AA(*i) + BB(*i), name="T")
+    C = te.compute(A.shape, lambda *i: T(*i), name="C")
+
+    sch = tvm.s_tir.Schedule(te.create_prim_func([A, B, C]))
+    xo, xi = sch.split(sch.get_loops("C")[0], factors=[None, 4])
+    sch.parallel(xo)
+    sch.vectorize(xi)
+
+    def check_llvm():
+        # BUILD and invoke the kernel.
+        f = tvm.compile(sch.mod, target="llvm")
+        dev = tvm.cpu(0)
+        # launch the kernel.
+        n = nn
+        a = tvm.runtime.tensor(np.random.uniform(size=n).astype(A.dtype), dev)
+        b = tvm.runtime.tensor(np.random.uniform(size=n).astype(B.dtype), dev)
+        c = tvm.runtime.tensor(np.zeros(n, dtype=C.dtype), dev)
+        f(a, b, c)
+        tvm.testing.assert_allclose(c.numpy(), a.numpy() + b.numpy())
+
+    check_llvm()