File size: 6,152 Bytes
fd684da | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 | """Evaluate CIFAR-10 checkpoints with independent per-GPU seeds."""
import argparse
import csv
import hashlib
import io
import json
import os
from pathlib import Path
import subprocess
import sys
import time
ROOT = Path(__file__).resolve().parents[1]
# Method names match configuration prefixes and checkpoint filenames.
CONFIGS = {
"baseline": "baseline_ar.yaml",
"tail_dropout": "tail_dropout_ar.yaml",
"flow_matching": "flow_matching_ar.yaml",
"flow_matching_tail_dropout": "flow_matching_tail_dropout_ar.yaml",
"flow_matching_tied_tail_dropout": "flow_matching_tied_tail_dropout_ar.yaml",
"war": "war_ar.yaml"
}
def sha256(path):
digest = hashlib.sha256()
with open(path, 'rb') as f:
for block in iter(lambda: f.read(8 * 1024 * 1024), b''):
digest.update(block)
return digest.hexdigest()
def check_free(gpus):
output = subprocess.check_output(
['nvidia-smi', '--query-gpu=index,memory.used,utilization.gpu',
'--format=csv,noheader,nounits'], text=True)
devices = {int(row[0]): (int(row[1]), int(row[2]))
for row in csv.reader(io.StringIO(output))}
busy = {gpu: devices.get(gpu) for gpu in gpus
if gpu not in devices or devices[gpu][0] > 100 or devices[gpu][1] > 0}
if busy:
raise RuntimeError(f'Requested GPUs are not free: {busy}')
def save_summary(output, rows):
(output / 'results.json').write_text(json.dumps(rows, indent=2) + '\n')
if rows:
with (output / 'results.csv').open('w', newline='') as f:
writer = csv.DictWriter(f, fieldnames=list(rows[0]))
writer.writeheader()
writer.writerows(rows)
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('--gpus', default='0,1,2,3,4,5,6,7')
parser.add_argument('--output', default='outputs/cifar10-nonlegacy')
parser.add_argument('--methods', nargs='+', choices=CONFIGS,
help='Optional subset, e.g. baseline war')
parser.add_argument('--resume', action='store_true', help='Reuse matching completed evaluations')
args = parser.parse_args()
gpus = [int(x) for x in args.gpus.split(',')]
if not gpus or len(gpus) != len(set(gpus)):
parser.error('GPU IDs must be nonempty and distinct')
configs = {key: ROOT / 'configs/cifar10' / name for key, name in CONFIGS.items()}
for config in configs.values():
if not config.is_file():
raise FileNotFoundError(config)
if args.methods:
if set(args.methods) - configs.keys():
parser.error('Unknown method')
configs = {key: path for key, path in configs.items() if key in args.methods}
checkpoints = {key: ROOT / 'checkpoints' / f'{key}.pt' for key in configs}
for checkpoint in checkpoints.values():
if not checkpoint.is_file():
raise FileNotFoundError(f'Place the downloaded checkpoint at {checkpoint}')
reference = ROOT / 'refs/cifar10-32x32_local.npz'
reference_hash = sha256(reference)
if reference_hash != '5493968c4f29b2878f64d6a640351f377e32e86553db56eca8147a0ae50d93f2':
raise ValueError('The CIFAR-10 FID reference checksum does not match')
output = Path(args.output).resolve()
output.mkdir(parents=True, exist_ok=True)
env = os.environ.copy()
env.update(CUDA_VISIBLE_DEVICES=','.join(map(str, gpus)), PYTHONDONTWRITEBYTECODE='1',
WANDB_MODE='disabled', OMP_NUM_THREADS='8', MKL_NUM_THREADS='8', TF_CPP_MIN_LOG_LEVEL='2')
rows = []
for key, config in configs.items():
checkpoint = checkpoints[key]
checkpoint_hash, config_hash = sha256(checkpoint), sha256(config)
case = output / key
result_path = case / 'metrics.json'
if result_path.exists() and not args.resume:
raise FileExistsError(result_path)
if not result_path.exists():
check_free(gpus)
case.mkdir(exist_ok=True)
cmd = [sys.executable, '-m', 'torch.distributed.run', '--standalone',
f'--nproc-per-node={len(gpus)}', 'evaluate.py', '--config', str(config),
'--checkpoint', str(checkpoint), '--num-samples', '50000', '--batch-size', '64',
'--seed', '42', '--no-legacy', '--output', str(case), '--fid-reference', str(reference)]
request = dict(command=cmd, checkpoint_sha256=checkpoint_hash,
config_sha256=config_hash, legacy=False)
(case / 'request.json').write_text(json.dumps(request, indent=2) + '\n')
print(f'START {key}', flush=True)
started = time.monotonic()
with (case / 'run.log').open('w') as log:
subprocess.run(cmd, cwd=ROOT, env=env, stdout=log, stderr=subprocess.STDOUT, check=True)
print(f'DONE {key} in {time.monotonic() - started:.1f}s', flush=True)
result = json.loads(result_path.read_text())
request = json.loads((case / 'request.json').read_text())
if request['checkpoint_sha256'] != checkpoint_hash:
raise ValueError(f'{key}: checkpoint changed since the recorded evaluation')
expected = dict(legacy=False, num_samples=50000, seed=42, world_size=len(gpus),
batch_size=64, ar_ema=True, precision='32-true', decoder='single_step',
config_sha256=config_hash, reference_sha256=reference_hash)
if any(result.get(name) != value for name, value in expected.items()):
raise ValueError(f'{key}: recorded evaluation settings do not match')
row = dict(method=key, nonlegacy_gfid=result['fid'], unique_images=result['unique_images'],
num_samples=result['num_samples'], legacy=False,
checkpoint_sha256=checkpoint_hash, config_sha256=config_hash,
reference_sha256=reference_hash)
rows.append(row)
save_summary(output, rows)
print(f'RESULT {key}: {result["fid"]:.8f}', flush=True)
print(f'COMPLETE: {len(rows)} non-legacy evaluations', flush=True)
if __name__ == '__main__':
main()
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