def decide(detmaster: str, experiment_id: int, model_name: str) -> bool:
# Submit determined experiment via CLI
from determined.experimental import Determined
import os
os.environ['DET_MASTER'] = detmaster
def get_validation_metric(checkpoint):
metrics = checkpoint.validation['metrics']
config = checkpoint.experiment_config
searcher = config['searcher']
smaller_is_better = bool(searcher['smaller_is_better'])
metric_name = searcher['metric']
if 'validation_metrics' in metrics:
metric = metrics['validation_metrics'][metric_name]
else:
metric = metrics['validationMetrics'][metric_name]
return (metric, smaller_is_better)
d = Determined()
checkpoint = d.get_experiment(experiment_id).top_checkpoint()
metric, smaller_is_better = get_validation_metric(checkpoint)
models = d.get_models(name=model_name)
model = None
for m in models:
if m.name == model_name:
model = m
break
if not model:
print(f'Registering new Model: {model_name}')
model = Determined().create_model(model_name)
model.register_version(checkpoint.uuid)
better = True
else:
latest_version = model.get_version()
if latest_version is None:
print(f'Registering new version: {model_name}')
model.register_version(checkpoint.uuid)
better = True
else:
old_metric, _ = get_validation_metric(latest_version)
if smaller_is_better:
if metric < old_metric:
print(f'Registering new version: {model_name}')
model.register_version(checkpoint.uuid)
better = True
else:
better = False
else:
if metric > old_metric:
print(f'Registering new version: {model_name}')
model.register_version(checkpoint.uuid)
better = True
else:
better = False
if not better:
print('Previous model version was better, logging...')
return better
def main():
parser = argparse.ArgumentParser(description='Run Determined Example')
parser.add_argument('experiment_id',
type=str,
help='path to context directory')
parser.add_argument('model_name',
type=str,
help='path to context directory')
args = parser.parse_args()
checkpoint = Determined().get_experiment(
args.experiment_id).top_checkpoint()
metric, smaller_is_better = get_validation_metric(checkpoint)
models = Determined().get_models(name=args.model_name)
model = None
for m in models:
if m.name == args.model_name:
model = m
break
if not model:
print(f'Registering new Model: {args.model_name}')
model = Determined().create_model(args.model_name)
model.register_version(checkpoint.uuid)
better = True
else:
latest_version = model.get_version()
if latest_version is None:
print(f'Registering new version: {args.model_name}')
model.register_version(checkpoint.uuid)
better = True
else:
old_metric, _ = get_validation_metric(latest_version)
if smaller_is_better:
if metric < old_metric:
print(f'Registering new version: {args.model_name}')
model.register_version(checkpoint.uuid)
better = True
else:
better = False
else:
if metric > old_metric:
print(f'Registering new version: {args.model_name}')
model.register_version(checkpoint.uuid)
better = True
else:
better = False
if not better:
print('Previous model version was better, logging...')
# Write experiment id to output file
with open('/tmp/decision.txt', 'w') as f:
if better:
f.write('yes')
else:
f.write('no')