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 +1,122 @@
+# 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 pytest
+
+import tvm
+from tvm.script import tirx as T
+from tvm.testing import env
+
+
+def run_test_break_continue(func, shape, expected):
+    target = tvm.target.Target("cuda")
+    mod = tvm.IRModule({"main": func})
+    with target:
+        mod = tvm.compile(mod, target=target, tir_pipeline="tirx")
+    arr_np = np.zeros(shape, dtype="int32")
+
+    def run_and_check():
+        dev = tvm.cuda(0)
+        arr = tvm.runtime.tensor(arr_np, device=dev)
+        mod(arr)
+        np.testing.assert_allclose(arr.numpy(), expected)
+
+    tvm.testing.run_with_gpu_lock(run_and_check)
+
+
+@pytest.mark.gpu
+@pytest.mark.skipif(not env.has_cuda(), reason="need cuda")
+def test_break_continue1():
+    # fmt: off
+    @T.prim_func
+    def func(A_ptr: T.handle):
+        A = T.match_buffer(A_ptr, (10,), "int32")
+
+        T.device_entry()
+        cta_id = T.cta_id([1])
+        tid = T.thread_id([32])
+        for i in T.serial(10):
+            if i == 2:
+                continue
+            if i == 7:
+                break
+            A[i] = i
+        # fmt: on
+
+    expected = np.array([0, 1, 0, 3, 4, 5, 6, 0, 0, 0], dtype="int32")
+    run_test_break_continue(func, (10,), expected)
+
+
+@pytest.mark.gpu
+@pytest.mark.skipif(not env.has_cuda(), reason="need cuda")
+def test_break_continue2():
+    # fmt: off
+    @T.prim_func
+    def func(A_ptr: T.handle):
+        A = T.match_buffer(A_ptr, (9,), "int32")
+
+        T.device_entry()
+        cta_id = T.cta_id([1])
+        tid = T.thread_id([32])
+        idx = T.alloc_buffer((1,), "int32", scope="local")
+        idx[0] = 0
+        for i in T.serial(3):
+            if i == 0:
+                idx[0] += 1
+                continue
+            for j in T.serial(3):
+                A[idx[0]] = i * 10 + j
+                idx[0] += 1
+                if j == 1:
+                    break
+        # fmt: on
+
+    expected = np.array([0, 10, 11, 20, 21, 0, 0, 0, 0], dtype="int32")
+    run_test_break_continue(func, (9,), expected)
+
+
+@pytest.mark.gpu
+@pytest.mark.skipif(not env.has_cuda(), reason="need cuda")
+def test_break_continue3():
+    # fmt: off
+    @T.prim_func
+    def func(A_ptr: T.handle):
+        A = T.match_buffer(A_ptr, (10,), "int32")
+
+        T.device_entry()
+        cta_id = T.cta_id([1])
+        tid = T.thread_id([32])
+        i = T.alloc_buffer((1,), "int32", scope="local")
+        i[0] = 0
+        while i[0] < 10:
+            if (i[0] % 2) == 1:
+                i[0] += 1
+                continue
+            A[i[0]] = i[0]
+            i[0] += 1
+            if i[0] == 7:
+                break
+        # fmt: on
+
+    expected = np.array([0, 0, 2, 0, 4, 0, 6, 0, 0, 0], dtype="int32")
+    run_test_break_continue(func, (10,), expected)
+
+
+if __name__ == "__main__":
+    test_break_continue1()
+    test_break_continue2()
+    test_break_continue3()