chore: import upstream snapshot with attribution

python/tvm/s_tir/schedule/transform.py

@@ -0,0 +1,46 @@
+# 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.
+"""Transformation on TIR schedule."""
+
+from tvm.s_tir.schedule import LoopRV, SBlockRV, Schedule
+
+from . import _ffi_api
+
+
+def tile_with_tensor_intrin(
+    sch: Schedule, block: SBlockRV, intrin_name: str, allow_padding: bool = False
+) -> LoopRV | None:
+    """Tile a subset of loops in the block according to the given tensor intrinsic.
+
+    Parameters
+    ----------
+    sch : Schedule
+        The schedule to which tiling is applied
+    block : SBlockRV
+        The block whose subset of loops will be tiled
+    intrin_name : str
+        The name of a tensor intrinsic, must be registerd via TensorIntrin.register(...) beforehand
+    allow_padding : bool
+        Whether to allow padding when tiling
+
+    Returns
+    -------
+    tiled_loop_rv : Optional[LoopRV]
+        LoopRV corresponding to the outermost loop of a block tiled according to the given intrin
+        std::nullopt if no valid loop mapping is found
+    """
+    return _ffi_api.TileWithTensorIntrin(sch, block, intrin_name, allow_padding)  # type: ignore