def describe(args: Namespace) -> None:
model = Determined(args.master, None).get_model(args.name)
if args.json:
print(json.dumps(model.to_json(), indent=2))
else:
render_model(model)
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)
return
print("Local checkpoint path:")
print(path, "\n")
# Print information about the downloaded step/checkpoint.
table = [
["Batch #", checkpoint.batch_number],
["Start Time", render.format_time(checkpoint.start_time)],
["End Time", render.format_time(checkpoint.end_time)],
["Checkpoint UUID", checkpoint.uuid],
["Validation Metrics", format_validation(checkpoint.validation)[1]],
]
headers, values = zip(*table) # type: ignore
render.tabulate_or_csv(headers, [values], False)
def describe(args: Namespace) -> None:
model = Determined(args.master, None).get_model(args.name)
ckpt = model.get_version()
if args.json:
print(json.dumps(model.to_json(), indent=2))
else:
render_model(model)
headers = [
"Version #",
"Trial ID",
"Batch #",
"Checkpoint UUID",
"Validation Metrics",
"Metadata",
]
print("\n")
values = [[
ckpt.version,
ckpt.trial_id,
ckpt.batch_number,
ckpt.uuid,
json.dumps(ckpt.validation, indent=2),
json.dumps(ckpt.metadata, indent=2),
]]
render.tabulate_or_csv(headers, values, False)
def list_versions(args: Namespace) -> None:
if args.json:
r = api.get(args.master, "models/{}/versions".format(args.name))
data = r.json()
print(json.dumps(data, indent=2))
else:
model = Determined(args.master).get_model(args.name)
render_model(model)
print("\n")
headers = [
"Version #",
"Trial ID",
"Batch #",
"Checkpoint UUID",
"Validation Metrics",
"Metadata",
]
values = [[
ckpt.version,
ckpt.trial_id,
ckpt.batch_number,
ckpt.uuid,
json.dumps(ckpt.validation, indent=2),
json.dumps(ckpt.metadata, indent=2),
] for ckpt in model.get_versions()]
render.tabulate_or_csv(headers, values, False)
def create(args: Namespace) -> None:
model = Determined(args.master, None).create_model(args.name,
args.description)
if args.json:
print(json.dumps(model.to_json(), indent=2))
else:
render_model(model)
def download(args: Namespace) -> None:
checkpoint = Determined(args.master, None).get_checkpoint(args.uuid)
path = checkpoint.download(path=args.output_dir)
if args.quiet:
print(path)
else:
render_checkpoint(checkpoint, path)
def describe(args: Namespace) -> None:
model = Determined(args.master, None).get_model(args.name)
checkpoint = model.get_version()
if args.json:
print(json.dumps(model.to_json(), indent=2))
else:
render_model(model)
print("\n")
render_model_version(checkpoint)
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 register_version(args: Namespace) -> None:
if args.json:
resp = api.post(
args.master,
"/api/v1/models/{}/versions".format(args.name),
body={"checkpoint_uuid": args.uuid},
)
print(json.dumps(resp.json(), indent=2))
else:
model = Determined(args.master, None).get_model(args.name)
checkpoint = model.register_version(args.uuid)
render_model(model)
print("\n")
render_model_version(checkpoint)
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