chore: import upstream snapshot with attribution

tests/python/tvmscript/test_tvmscript_regression.py

@@ -0,0 +1,94 @@
+# 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: F841
+import numpy
+
+import tvm
+import tvm.testing
+from tvm.script import tirx as T
+
+# This numpy array is used to test the comparison between the global objects and the
+# `tvm.script.tirx` submodule.
+np_array = numpy.array([0, 1, 2, 3])
+
+
+@T.prim_func(s_tir=True)
+def matmul(a: T.handle, b: T.handle, c: T.handle) -> None:
+    A = T.match_buffer(a, [128, 128])
+    B = T.match_buffer(b, [128, 128])
+    C = T.match_buffer(c, [128, 128])
+
+    for i, j, k in T.grid(128, 128, 128):
+        with T.sblock("update"):
+            vi, vj, vk = T.axis.remap("SSR", [i, j, k])
+            with T.init():
+                C[vi, vj] = T.float32(0)
+            C[vi, vj] = C[vi, vj] + A[vi, vk] * B[vj, vk]
+
+
+def test_multi_element_array_in_outmost_namespace():
+    func = matmul
+    rt_func = tvm.script.from_source(func.script())
+    tvm.ir.assert_structural_equal(func, rt_func)
+
+
+def test_different_dtype_assignment_to_var():
+    @T.prim_func(s_tir=True)
+    def test_case():
+        a = T.sblock_alloc_buffer((10, 10), dtype="int8")
+
+    @T.prim_func(s_tir=True)
+    def func_ref():
+        a = T.sblock_alloc_buffer([10, 10], dtype="int8")
+        T.evaluate(0)
+
+    tvm.ir.assert_structural_equal(
+        test_case.with_attr("global_symbol", "main"), func_ref.with_attr("global_symbol", "main")
+    )
+
+
+def test_var_capturing_order():
+    b = 2
+
+    @T.prim_func(s_tir=True)
+    def test_case():
+        k: T.let[T.int32] = b
+
+    @T.prim_func(s_tir=True)
+    def func_ref():
+        k: T.let[T.int32] = 2
+        T.evaluate(0)
+
+    tvm.ir.assert_structural_equal(
+        test_case.with_attr("global_symbol", "main"), func_ref.with_attr("global_symbol", "main")
+    )
+
+
+def test_tir_buffer_region_extent_correct_dtype():
+    @T.prim_func(s_tir=True)
+    def func(A: T.Buffer((T.int64(16), T.int64(1)), "float32")):
+        for i in T.grid(T.int64(16)):
+            with T.sblock("block"):
+                vi = T.axis.remap("S", [i])
+                T.reads(A[vi, T.int64(0) : T.int64(1)])
+                T.evaluate(0)
+
+    assert func.body.block.body.body.block.reads[0].region[0].extent.ty.dtype == "int64"
+
+
+if __name__ == "__main__":
+    tvm.testing.main()