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