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[CK_TILE] Integrate CK Tile Dispatcher code generation into CK Tile Profiler (#7284) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ## Motivation CK Tile is going to be delivered to hipDNN via CK Dispatcher. Currently the CK Tile Profiler using CK Builder for generating the profiled instances from the configuration files that identify the instances that old CK exposes. We need to replace this instance generation with the CK Tile Dispatcher codegen. ## Technical Details The old CK Profiler config files are converted to JSON files that the CK Tile Dispatcher can digest. The conversion script for configurations is stored to source control in case we need to update the JSON configurations later. The dispatcher generates instance libraries per conv direction (fwd, bwd data, and bwd weight) that are linked to the CK Profiler executable. I also implemented codegne for the stream-K and depthwise conv instances. The proposed solution replaces the CK Builder codegen with the CK Tile Dispatcher codegen. There are two new methods that are exposed via the dispatcher backend - `is_supported` - required to enabled the profiler workflow where we check the applicability of the kernel instance before running it. - `get_instance_string` - this mainly for verification. This provide the CK Builder instance string for verifying that the old CK Builder based profiler and the new CK Tile Dispatcher based profiler have the same instances. The rules that limit the generated instances are now collected to a single location under the dispacther. The CK Builder codegen uses these, which ensures that the two codegen pipelines are in sync. The next step (different PR) is to remove the CK Builder codegen pipeline altogether. ## Test Plan Verified that the old CK Builder based profiler and the new CK Tile Dispatcher based profiler have the same instances, that is, the Dispatcher based codgen can generate the same instances as the old CK Builder. ## Submission Checklist - [x] Look over the contributing guidelines at https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
172 lines
6.4 KiB
Python
Executable File
172 lines
6.4 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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# SPDX-License-Identifier: MIT
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#
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# Generates dispatcher-based kernels for the CK Profiler (all directions).
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#
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# This script:
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# 1. Reads JSON config files
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# 2. Calls load_configs_from_json + UnifiedGroupedConvCodegen.generate_all() for each JSON
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# 3. Generates include_all_grouped_conv_<variant>_kernels.hpp
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# 4. Generates chunked register_*_chunk_N.cpp files + register_all_grouped_conv_kernels.cpp
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#
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# Usage:
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# python3 generate_profiler_kernels.py \
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# --variant {fwd,bwd_data,bwd_weight} \
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# --config-dir <path-to-json-configs> \
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# --codegen <path-to-unified_grouped_conv_codegen.py> \
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# --output-dir <generated-kernel-output-dir> \
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# --arch gfx950 \
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# [--config-set tests|profiler]
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import argparse
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import sys
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from pathlib import Path
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from registration_codegen import generate_chunked_registration
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VARIANT_CONFIG = {
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"fwd": {
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"glob_pattern": "grouped_conv_fwd_*.hpp",
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"include_all_header": "include_all_grouped_conv_fwd_kernels.hpp",
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"description": "forward",
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"op_enum": "GroupedConvOp::Forward",
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"run_fn_maker": "backends::make_conv_fwd_run_fn",
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"is_supported_fn_maker": "backends::make_conv_fwd_is_supported_fn",
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"register_fn_name": "register_all_grouped_conv_fwd_kernels",
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},
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"bwd_data": {
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"glob_pattern": "grouped_conv_bwd_data_*.hpp",
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"include_all_header": "include_all_grouped_conv_bwd_data_kernels.hpp",
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"description": "backward data",
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"op_enum": "GroupedConvOp::BackwardData",
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"run_fn_maker": "backends::make_conv_bwd_data_run_fn",
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"is_supported_fn_maker": "backends::make_conv_bwd_data_is_supported_fn",
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"register_fn_name": "register_all_grouped_conv_bwd_data_kernels",
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},
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"bwd_weight": {
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"glob_pattern": "grouped_conv_bwd_weight_*.hpp",
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"include_all_header": "include_all_grouped_conv_bwd_weight_kernels.hpp",
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"description": "backward weight",
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"op_enum": "GroupedConvOp::BackwardWeight",
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"run_fn_maker": "backends::make_conv_bwd_weight_run_fn",
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"is_supported_fn_maker": "backends::make_conv_bwd_weight_is_supported_fn",
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"register_fn_name": "register_all_grouped_conv_bwd_weight_kernels",
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},
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}
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def generate_kernels_from_config(config_file, output_dir, arch):
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"""Generate kernels for a single JSON config via direct Python API."""
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import json
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from unified_grouped_conv_codegen import UnifiedGroupedConvCodegen, load_configs_from_json
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try:
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configs = load_configs_from_json(config_file, arch=arch)
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# Extract datatype from JSON config (matches old --config-file behavior)
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with open(config_file, "r") as f:
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config_data = json.load(f)
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datatype = config_data["datatype"]
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# The JSON configs are valid for all architectures.
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# Hence, disable the arch_filter.
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codegen = UnifiedGroupedConvCodegen(output_dir=output_dir, gpu_target=arch, enable_arch_filter=False)
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codegen.generate_all(configs, datatypes=[datatype])
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return True
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except Exception as e:
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print(f"ERROR generating from {config_file}: {e}", file=sys.stderr)
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return False
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def collect_kernel_headers(output_dir, glob_pattern):
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"""Collect all generated .hpp kernel headers matching the variant pattern."""
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headers = sorted(Path(output_dir).glob(glob_pattern))
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return headers
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def generate_include_all_header(headers, output_dir, header_filename, description):
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"""Generate include_all_grouped_conv_<variant>_kernels.hpp."""
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lines = [
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"// Auto-generated \u2014 do not edit",
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f"// Includes all generated {description} kernel headers.",
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"#pragma once",
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"",
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]
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for h in headers:
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lines.append(f'#include "{h.name}"')
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lines.append("")
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path = Path(output_dir) / header_filename
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path.write_text("\n".join(lines))
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print(f"Generated {path} ({len(headers)} includes)")
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return path
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def main():
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parser = argparse.ArgumentParser(
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description="Generate dispatcher-based kernels for CK Profiler."
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)
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parser.add_argument("--variant", required=True, choices=list(VARIANT_CONFIG.keys()))
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parser.add_argument("--config-dir", required=True)
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parser.add_argument("--codegen", required=True)
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parser.add_argument("--output-dir", required=True)
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parser.add_argument("--arch", default="gfx950")
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parser.add_argument("--config-set", default="tests", choices=["tests", "profiler"])
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args = parser.parse_args()
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cfg = VARIANT_CONFIG[args.variant]
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config_dir = Path(args.config_dir) / args.config_set
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codegen_path = Path(args.codegen)
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output_dir = Path(args.output_dir)
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output_dir.mkdir(parents=True, exist_ok=True)
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# Add the codegen directory to sys.path so unified_grouped_conv_codegen
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# and its siblings are importable regardless of working directory.
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codegen_dir = str(codegen_path.parent.resolve())
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if codegen_dir not in sys.path:
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sys.path.insert(0, codegen_dir)
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if not config_dir.exists():
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print(f"ERROR: Config directory not found: {config_dir}", file=sys.stderr)
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sys.exit(1)
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json_configs = sorted(config_dir.glob("*.json"))
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if not json_configs:
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print(f"ERROR: No JSON config files in {config_dir}", file=sys.stderr)
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sys.exit(1)
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print(f"Found {len(json_configs)} config files in {config_dir}")
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success = True
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for config_file in json_configs:
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print(f"Generating from {config_file.name}...")
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if not generate_kernels_from_config(config_file, output_dir, args.arch):
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success = False
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if not success:
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print("ERROR: Some kernel generations failed", file=sys.stderr)
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sys.exit(1)
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headers = collect_kernel_headers(output_dir, cfg["glob_pattern"])
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print(f"Found {len(headers)} generated kernel headers")
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if not headers:
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print("ERROR: No kernel headers generated", file=sys.stderr)
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sys.exit(1)
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generate_include_all_header(headers, output_dir, cfg["include_all_header"], cfg["description"])
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generate_chunked_registration(
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headers, output_dir,
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variant=args.variant,
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op_enum=cfg["op_enum"],
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run_fn_maker=cfg["run_fn_maker"],
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is_supported_fn_maker=cfg["is_supported_fn_maker"],
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register_fn_name=cfg["register_fn_name"],
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)
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print(f"\nDone. {len(headers)} kernels ready in {output_dir}")
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if __name__ == "__main__":
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main()
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