chore: import upstream snapshot with attribution

tests/python/ir/test_pass_instrument.py

@@ -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: E741
+"""Instrument test cases."""
+
+import tvm
+from tvm import relax
+from tvm.ir.instrument import PrintAfterAll, PrintBeforeAll
+from tvm.script import ir as I
+from tvm.script import relax as R
+from tvm.script import tirx as T
+
+# pylint: disable=invalid-name,missing-function-docstring,no-value-for-parameter
+
+
+def test_tir_print_all_passes(capsys):
+    @T.prim_func(s_tir=True)
+    def func(a: T.handle, b: T.handle) -> None:
+        A = T.match_buffer(a, (128, 128, 128, 128))
+        B = T.match_buffer(b, (128, 128, 128, 128))
+        for i, j, k, l in T.grid(128, 128, 128, 128):
+            with T.sblock("B"):
+                vi, vj, vk, vl = T.axis.remap("SSSS", [i, j, k, l])
+                B[vi, vj, vk, vl] = A[vi, vj, vk, vl] * 2.0
+
+    with tvm.transform.PassContext(opt_level=3, instruments=[PrintBeforeAll(), PrintAfterAll()]):
+        tvm.compile(func)
+    all_passes_output = capsys.readouterr().out
+    assert "Before Running Pass:" in all_passes_output
+    assert "After Running Pass:" in all_passes_output
+    assert 'name="tirx.' in all_passes_output
+
+
+def test_relax_print_all_passes(capsys):
+    @I.ir_module(s_tir=True)
+    class Module:
+        @R.function
+        def func(x: R.Tensor((16,), "float32"), y: R.Tensor((16,), "float32")):
+            z = R.add(x, y)
+            y = z
+            return y
+
+    pipeline = relax.get_pipeline("default_build")
+    with tvm.transform.PassContext(opt_level=3, instruments=[PrintBeforeAll(), PrintAfterAll()]):
+        pipeline(Module)
+    all_passes_output = capsys.readouterr().out
+    assert "Before Running Pass:" in all_passes_output
+    assert "After Running Pass:" in all_passes_output
+    assert 'name="_pipeline"' in all_passes_output