def main():
try:
parser = get_args_parser()
args = parser.parse_args()
if args.command == "predict_proba":
predict_proba(args.input_path, args.model_path, args.device)
elif args.command == "predict":
print(predict(args.input_path, args.model_path, args.device))
elif args.command == "learn":
learn(args.location, args.num_samples, args.device)
elif args.command == "crossval":
crossval(path=args.model_path)
elif args.command in ["locations", "ls"]:
locations(args.model_path)
elif args.command == "rename":
rename_label(args.label, args.new_label)
print("Retraining model...")
train_model()
elif args.command == "train":
train_model(args.model_path)
else:
parser.print_help()
parser.exit(1)
except (KeyboardInterrupt, SystemExit):
exit()
def main():
if "predict_proba" == sys.argv[1]:
predict_proba()
elif "predict" == sys.argv[1]:
predict()
elif "learn" in sys.argv[1] and len(sys.argv) == 4:
category = sys.argv[2]
n = int(sys.argv[3])
learn(category, n)
elif "crossval" in sys.argv[1]:
crossval()
def main():
parser = get_args_parser()
args = parser.parse_args()
if args.command == "predict_proba":
predict_proba()
elif args.command == "predict":
predict()
elif args.command == "learn":
learn(args.location, args.num_samples)
elif args.command == "crossval":
crossval()
else:
parser.print_help()
parser.exit(1)
def main():
parser = get_args_parser()
args = parser.parse_args()
if args.command == "predict_proba":
predict_proba()
elif args.command == "predict":
predict()
elif args.command == "learn":
learn(args.location, args.num_samples)
elif args.command == "crossval":
crossval()
elif args.command == "locations":
locations()
else:
parser.print_help()
parser.exit(1)
def main():
parser = get_args_parser()
args = parser.parse_args()
if args.command == "predict_proba":
predict_proba()
elif args.command == "predict":
print(predict())
elif args.command == "learn":
learn(args.location, args.num_samples)
elif args.command == "crossval":
crossval()
elif args.command in ["locations", "ls"]:
locations()
elif args.command == "rename":
rename_label(args.label, args.new_label)
print("Retraining model...")
train_model()
else:
parser.print_help()
parser.exit(1)
def test_crossval():
X, y = mock_get_train_data()
pipeline = mock_get_model()
return crossval(pipeline, X, y, folds=2, n=1)
def test_crossval():
X, y = mock_get_train_data()
pipeline = mock_get_model()
assert crossval(pipeline, X, y, folds=2, n=1)