def test_hosting_start(start_model_server): from sagemaker_pytorch_serving_container import serving serving.main() start_model_server.assert_called_with( handler_service='sagemaker_pytorch_serving_container.handler_service')
import shlex import subprocess import sys import os.path if not os.path.exists("/opt/ml/input/config"): subprocess.call([ 'python', '/usr/local/bin/deep_learning_container.py', '&>/dev/null', '&' ]) if sys.argv[1] == 'serve': from sagemaker_pytorch_serving_container import serving serving.main() else: subprocess.check_call(shlex.split(' '.join(sys.argv[1:]))) # prevent docker exit subprocess.call(['tail', '-f', '/dev/null'])
def test_hosting_start(start_torchserve): from sagemaker_pytorch_serving_container import serving serving.main() start_torchserve.assert_called()