in tensorflow-train-in-sagemaker-deploy-with-lambda/mnist-2.py [0:0]
def _parse_args():
parser = argparse.ArgumentParser()
# Data, model, and output directories
# model_dir is always passed in from SageMaker. By default this is a S3 path under the default bucket.
parser.add_argument('--model_dir', type=str)
parser.add_argument('--sm-model-dir', type=str, default=os.environ.get('SM_MODEL_DIR'))
parser.add_argument('--train', type=str, default=os.environ.get('SM_CHANNEL_TRAINING'))
parser.add_argument('--hosts', type=list, default=json.loads(os.environ.get('SM_HOSTS')))
parser.add_argument('--current-host', type=str, default=os.environ.get('SM_CURRENT_HOST'))
return parser.parse_known_args()