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gen_oplist.py
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#!/usr/bin/env python3
import argparse
import json
import os
import sys
from functools import reduce
from typing import Any, List, Set
import yaml
from tools.lite_interpreter.gen_selected_mobile_ops_header import (
write_selected_mobile_ops,
)
from torchgen.selective_build.selector import (
combine_selective_builders,
SelectiveBuilder,
)
def extract_all_operators(selective_builder: SelectiveBuilder) -> Set[str]:
return set(selective_builder.operators.keys())
def extract_training_operators(selective_builder: SelectiveBuilder) -> Set[str]:
ops = []
for op_name, op in selective_builder.operators.items():
if op.is_used_for_training:
ops.append(op_name)
return set(ops)
def throw_if_any_op_includes_overloads(selective_builder: SelectiveBuilder) -> None:
ops = []
for op_name, op in selective_builder.operators.items():
if op.include_all_overloads:
ops.append(op_name)
if ops:
raise Exception( # noqa: TRY002
(
"Operators that include all overloads are "
+ "not allowed since --allow-include-all-overloads "
+ "was specified: {}"
).format(", ".join(ops))
)
def gen_supported_mobile_models(model_dicts: List[Any], output_dir: str) -> None:
supported_mobile_models_source = """/*
* Generated by gen_oplist.py
*/
#include "fb/supported_mobile_models/SupportedMobileModels.h"
struct SupportedMobileModelCheckerRegistry {{
SupportedMobileModelCheckerRegistry() {{
auto& ref = facebook::pytorch::supported_model::SupportedMobileModelChecker::singleton();
ref.set_supported_md5_hashes(std::unordered_set<std::string>{{
{supported_hashes_template}
}});
}}
}};
// This is a global object, initializing which causes the registration to happen.
SupportedMobileModelCheckerRegistry register_model_versions;
"""
# Generate SupportedMobileModelsRegistration.cpp
md5_hashes = set()
for model_dict in model_dicts:
if "debug_info" in model_dict:
debug_info = json.loads(model_dict["debug_info"][0])
if debug_info["is_new_style_rule"]:
for asset_info in debug_info["asset_info"].values():
md5_hashes.update(asset_info["md5_hash"])
supported_hashes = ""
for md5 in md5_hashes:
supported_hashes += f'"{md5}",\n'
with open(
os.path.join(output_dir, "SupportedMobileModelsRegistration.cpp"), "wb"
) as out_file:
source = supported_mobile_models_source.format(
supported_hashes_template=supported_hashes
)
out_file.write(source.encode("utf-8"))
def main(argv: List[Any]) -> None:
"""This binary generates 3 files:
1. selected_mobile_ops.h: Primary operators used by templated selective build and Kernel Function
dtypes captured by tracing
2. selected_operators.yaml: Selected root and non-root operators (either via tracing or static analysis)
"""
parser = argparse.ArgumentParser(description="Generate operator lists")
parser.add_argument(
"--output-dir",
"--output_dir",
help=(
"The directory to store the output yaml files (selected_mobile_ops.h, "
+ "selected_kernel_dtypes.h, selected_operators.yaml)"
),
required=True,
)
parser.add_argument(
"--model-file-list-path",
"--model_file_list_path",
help=(
"Path to a file that contains the locations of individual "
+ "model YAML files that contain the set of used operators. This "
+ "file path must have a leading @-symbol, which will be stripped "
+ "out before processing."
),
required=True,
)
parser.add_argument(
"--allow-include-all-overloads",
"--allow_include_all_overloads",
help=(
"Flag to allow operators that include all overloads. "
+ "If not set, operators registered without using the traced style will"
+ "break the build."
),
action="store_true",
default=False,
required=False,
)
options = parser.parse_args(argv)
if os.path.isfile(options.model_file_list_path):
print("Processing model file: ", options.model_file_list_path)
model_dicts = []
model_dict = yaml.safe_load(open(options.model_file_list_path))
model_dicts.append(model_dict)
else:
print("Processing model directory: ", options.model_file_list_path)
assert options.model_file_list_path[0] == "@"
model_file_list_path = options.model_file_list_path[1:]
model_dicts = []
with open(model_file_list_path) as model_list_file:
model_file_names = model_list_file.read().split()
for model_file_name in model_file_names:
with open(model_file_name, "rb") as model_file:
model_dict = yaml.safe_load(model_file)
model_dicts.append(model_dict)
selective_builders = [SelectiveBuilder.from_yaml_dict(m) for m in model_dicts]
# While we have the model_dicts generate the supported mobile models api
gen_supported_mobile_models(model_dicts, options.output_dir)
# We may have 0 selective builders since there may not be any viable
# pt_operator_library rule marked as a dep for the pt_operator_registry rule.
# This is potentially an error, and we should probably raise an assertion
# failure here. However, this needs to be investigated further.
selective_builder = SelectiveBuilder.from_yaml_dict({})
if len(selective_builders) > 0:
selective_builder = reduce(
combine_selective_builders,
selective_builders,
)
if not options.allow_include_all_overloads:
throw_if_any_op_includes_overloads(selective_builder)
with open(
os.path.join(options.output_dir, "selected_operators.yaml"), "wb"
) as out_file:
out_file.write(
yaml.safe_dump(
selective_builder.to_dict(), default_flow_style=False
).encode("utf-8"),
)
write_selected_mobile_ops(
os.path.join(options.output_dir, "selected_mobile_ops.h"),
selective_builder,
)
if __name__ == "__main__":
main(sys.argv[1:])