Files
composable_kernel/tile_engine/ops/reduce/reduce_instance_builder.py
damien-lejeune 4216d43da8 Dlejeune/ck tile 2d multiple reductions (#3147)
* WIP

* Add Unit tests for the Multi Reduction Kernel

* clang format

* Rename multiblock to threadwise

* Multiblock WIP

* Fix multi reduce multi block unit tests

* Multi Reduce Tile Engine: WIP

* refactoring + try addressing precision error

* Fix multiops examples

* Cleanup

* Clean up tile engine's reduce op

* Update changelog

* Fix remod/clang

* Fix dates

* Fix documentation & missing file

* Fix comments

* Use the update_tile api in the multi-block kernel

* Unify threadwise/multiblock into a single kernel + default multiblock output to float in tests

* Add TileParitioner

* Cleanup

* Add warning when no data to process, in the example

* Refactoring Reduce kernel Tile Partioner + cleanup

* Move the tile partioner to its own file

* Add missing includes

* Fix copyright header with update_amd_copyright_headers.py

* Fix change of interface in Reduce2dProblem

---------

Co-authored-by: Damien Lejeune <damien.lejeune@amd.com>
Co-authored-by: Adam Osewski <19374865+aosewski@users.noreply.github.com>
2026-01-09 11:16:37 +01:00

172 lines
6.1 KiB
Python

# Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
# SPDX-License-Identifier: MIT
import argparse
from pathlib import Path
from reduce_config import ReduceConfig
from reduce_parameter import get_parameter_combinations, TYPE_MAP
class MultiReduceBase:
def __init__(self, working_path, gpu_target, datatype, config_json=None):
self.working_path = Path(working_path)
self.gpu_target = gpu_target
self.datatype = datatype
self.output_type = self.datatype
self.config = ReduceConfig(config_json) if config_json else None
self.name = "multiops_base"
self.signature_test = {
3: "Test3D_KeepDim0_ReduceDim12",
4: "Test4D_KeepDim01_ReduceDim23",
}
self.header = "test_multi_reduce2d_multiblock_impl.hpp"
self.test_type = "TestCkTileMultiReduce2D"
def _generate_instances(self):
if not self.config:
raise ValueError("Configuration not provided.")
instances = []
for params in get_parameter_combinations(self.config.config_dict):
instance = self._create_instance(params)
instances.append((instance, params))
return instances
def _create_instance(self, parameters):
generated_test = self._get_test(parameters)
return generated_test
def do_list_blobs(self):
with open(
self.working_path / Path(f"reduce_{self.name}_blobs_list.txt"), "w"
) as f:
combos_str = [
f"{self.name}_{params}"
for params in get_parameter_combinations(self.config.config_dict)
]
f.write("\n".join(combos_str))
f.write("\n")
def do_generate_blobs(self):
instances = self._generate_instances()
for instance_code, params in instances:
blob_filename = self.working_path / Path(f"test_{self.name}_{params}.cpp")
with open(blob_filename, "w") as f:
f.write(instance_code)
def _get_test(self, params):
dimension = len(params.input_shape)
signature = self.signature_test.get(dimension, None)
if not signature:
raise ValueError(
f"No test signature found for input shape dimension: {dimension}"
)
shape_str = [str(i) for i in params.input_shape]
input_shape_arg_str = ",".join(shape_str)
input_shape_str = "x".join(shape_str)
t = f"""#include "{self.header}"
using Shape_BlockWarps = ck_tile::sequence<{params.warp_per_block_m}, {params.warp_per_block_n}>;
using Shape_BlockTile = ck_tile::sequence<{params.tile_m}, {params.tile_n}>;
using Shape_WarpTile = ck_tile::sequence<{params.warp_m}, {params.warp_n}>;
using Shape_ThreadTile = ck_tile::sequence<{params.thread_tile_m}, {params.thread_tile_n}>;
using TestConfig =
std::tuple<{TYPE_MAP[self.datatype]},
float,
{TYPE_MAP[self.output_type]},
ck_tile::tuple<ck_tile::ReduceOp::Add, ck_tile::ReduceOp::Add>, // Intra block reductions
ck_tile::tuple<ck_tile::element_wise::PassThrough, ck_tile::element_wise::UnarySquare>, // Elementwise ops
ck_tile::tuple<ck_tile::element_wise::PassThrough, ck_tile::element_wise::UnaryDivide>, // Accumulator Elementiwise ops, intra block
ck_tile::tuple<ck_tile::ReduceOp::Add, ck_tile::ReduceOp::Add>, // Inter block reduction
Shape_BlockWarps,
Shape_BlockTile,
Shape_WarpTile,
Shape_ThreadTile>;
// Register the type(s) for the typed test suite
typedef ::testing::Types<TestConfig> TestTypes;
TYPED_TEST_SUITE({self.test_type}, TestTypes);
TYPED_TEST({self.test_type}, {signature}_{input_shape_str})
{{
this->Run{signature}({input_shape_arg_str});
}}
"""
return t
class MultiReduceThreadwiseKernelBuilder(MultiReduceBase):
def __init__(self, working_path, gpu_target, datatype, config_json=None):
super().__init__(working_path, gpu_target, datatype, config_json)
self.name = "multiops_threadwise"
self.header = "test_multi_reduce2d_threadwise_impl.hpp"
self.test_type = "TestCkTileMultiReduceThreadwise"
class MultiReduceMultiBlockKernelBuilder(MultiReduceBase):
def __init__(self, working_path, gpu_target, datatype, config_json=None):
super().__init__(working_path, gpu_target, datatype, config_json)
self.name = "multiops_multiblock"
self.output_type = (
"float" # Force float to be used as the output is also used as accumulator
)
self.header = "test_multi_reduce2d_multiblock_impl.hpp"
self.test_type = "TestCkTileMultiReduceMultiblock"
def main(args):
variants = {
"multiops_threadwise": {"class": MultiReduceThreadwiseKernelBuilder},
"multiops_multiblock": {"class": MultiReduceMultiBlockKernelBuilder},
}
if not (args.list_blobs or args.gen_blobs):
raise ValueError("Please provide a list or generate blobs.")
builder = variants.get(args.variant)
builder_instance = builder["class"](
working_path=args.working_path,
gpu_target=args.gpu_target,
datatype=args.datatype,
config_json=args.config_json,
)
if args.list_blobs:
builder_instance.do_list_blobs()
if args.gen_blobs:
builder_instance.do_generate_blobs()
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Reduce Instance Builder")
parser.add_argument(
"--working_path", type=str, required=True, help="Working directory path"
)
parser.add_argument("--datatype", type=str, required=True, help="Data type")
parser.add_argument(
"--variant", type=str, required=True, help="Variant: multiblock or threadwise"
)
parser.add_argument(
"--config_json", type=str, required=True, help="Path to config JSON blob"
)
parser.add_argument("--list_blobs", action="store_true", help="List blobs")
parser.add_argument("--gen_blobs", action="store_true", help="Generate blobs")
parser.add_argument("--gpu_target", type=str, required=True, help="GPU target")
args = parser.parse_args()
main(args)