File size: 3,302 Bytes
4198d45 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 | #!/usr/bin/env python3
# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
"""Reproduce the paper's d=5/d=7, ten-round Google Willow evaluation."""
from __future__ import annotations
import argparse
import os
import shlex
import sys
from pathlib import Path
CODE_ROOT = Path(__file__).resolve().parents[1]
if str(CODE_ROOT) not in sys.path:
sys.path.insert(0, str(CODE_ROOT))
from scripts.qadapt_example_utils import ( # noqa: E402
add_common_inference_args,
checkpoint_specs,
parse_gpus,
)
def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"--benchmark-root",
type=Path,
default=Path("benchmarks/google_qec/google_105Q_surface_code_d3_d5_d7"),
)
parser.add_argument(
"--distances",
nargs="+",
type=int,
default=[5, 7],
help="Paper default: d=5 and d=7.",
)
parser.add_argument(
"--rounds",
nargs="+",
type=int,
default=[10],
help="Paper default: ten syndrome-extraction rounds.",
)
add_common_inference_args(
parser,
default_output_dir=Path("outputs/examples/released_models/willow"),
default_num_samples=0,
)
return parser.parse_args(argv)
def main(argv: list[str] | None = None) -> int:
args = parse_args(argv)
output_path = args.output_dir / "results.json"
if args.resume and output_path.is_file():
print(f"[resume] output exists: {output_path}")
return 0
selected_gpus = parse_gpus(args.gpus)
bases = ["X", "Z"] if args.basis == "both" else [args.basis]
specs = checkpoint_specs(args)
command_preview = [
str(args.python),
"-m",
"scripts.providers.google_qec_decoder_benchmark",
"--benchmark-root",
str(args.benchmark_root),
"--distances",
*(str(value) for value in args.distances),
"--rounds",
*(str(value) for value in args.rounds),
"--bases",
*bases,
"--models",
*(spec.name for spec in specs),
"--max-shots",
str(args.num_samples),
"--batch-size",
str(args.batch_size),
"--latency-shots",
str(args.latency_num_samples),
"--output",
str(output_path),
]
if args.dry_run:
print(
f"[dry-run] gpu={selected_gpus[0]} seed={args.seed} "
+ shlex.join(command_preview)
)
for spec in specs:
print(
f"[dry-run] model {spec.name}: "
f"model_id={spec.model_id} checkpoint={spec.checkpoint}"
)
return 0
os.environ["CUDA_VISIBLE_DEVICES"] = selected_gpus[0]
from scripts.providers import google_qec_decoder_benchmark as benchmark
benchmark.DEFAULT_MODELS = {
spec.name: benchmark.BenchmarkModel(
spec.name,
spec.model_id,
spec.checkpoint,
)
for spec in specs
}
benchmark.DEFAULT_BENCHMARK_ROOT = args.benchmark_root
return benchmark.main(command_preview[3:])
if __name__ == "__main__":
raise SystemExit(main())
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