def download(args: Namespace) -> None:
exp = Determined(args.master, args.user).get_experiment(args.experiment_id)
checkpoints = exp.top_n_checkpoints(
args.top_n,
sort_by=args.sort_by,
smaller_is_better=args.smaller_is_better)
top_level = pathlib.Path(args.output_dir)
top_level.mkdir(parents=True, exist_ok=True)
for ckpt in checkpoints:
path = ckpt.download(str(top_level.joinpath(ckpt.uuid)))
if args.quiet:
print(path)
else:
render_checkpoint(ckpt, path)
print()
def list_models(args: Namespace) -> None:
models = Determined(args.master, None).get_models(
sort_by=ModelSortBy[args.sort_by.upper()],
order_by=ModelOrderBy[args.order_by.upper()])
if args.json:
print(json.dumps([m.to_json() for m in models], indent=2))
else:
headers = ["Name", "Creation Time", "Last Updated Time", "Metadata"]
values = [[
m.name, m.creation_time, m.last_updated_time,
json.dumps(m.metadata or {}, indent=2)
] for m in models]
render.tabulate_or_csv(headers, values, False)
def download(args: Namespace) -> None:
checkpoint = (Determined(args.master,
None).get_trial(args.trial_id).select_checkpoint(
latest=args.latest,
best=args.best,
uuid=args.uuid,
sort_by=args.sort_by,
smaller_is_better=args.smaller_is_better,
))
path = checkpoint.download(path=args.output_dir)
if args.quiet:
print(path)
else:
render_checkpoint(checkpoint, path)
def describe(args: Namespace) -> None:
checkpoint = Determined(args.master, None).get_checkpoint(args.uuid)
render_checkpoint(checkpoint)
def export_model(experiment_id: int, master_url: str) -> tf.keras.Model:
checkpoint = (Determined(
master=master_url).get_experiment(experiment_id).top_checkpoint())
model = checkpoint.load()
return model
