def main():
args, extra = parse_args(sys.argv[1:])
# Pretrained Alibi explainer
alibi_model = None
keras_model = None
if args.storage_uri is not None:
path = kfserving.Storage.download(args.storage_uri)
alibi_model = os.path.join(path, EXPLAINER_FILENAME)
if os.path.exists(alibi_model):
with open(alibi_model, "rb") as f:
logging.info("Loading Alibi model")
alibi_model = dill.load(f)
else:
keras_path = os.path.join(path, KERAS_MODEL)
if os.path.exists(keras_path):
with open(keras_path, "rb") as f:
logging.info("Loading Keras model")
keras_model = keras.models.load_model(keras_path)
explainer = AlibiExplainer(args.model_name, args.predictor_host,
ExplainerMethod(args.command), extra,
alibi_model, Protocol(args.protocol),
args.tf_data_type, keras_model)
explainer.load()
ExplainerServer(args.http_port).start(explainer)
def main():
args, extra = parse_args(sys.argv[1:])
# Pretrained Alibi explainer
alibi_model = None
if args.storage_uri is not None:
alibi_model = os.path.join(
kfserving.Storage.download(args.storage_uri), EXPLAINER_FILENAME)
with open(alibi_model, "rb") as f:
logging.info("Loading Alibi model")
alibi_model = dill.load(f)
explainer = AlibiExplainer(
args.model_name,
args.predictor_host,
ExplainerMethod(args.command),
extra,
alibi_model,
)
explainer.load()
kfserving.KFServer().start(models=[explainer])
help='Explainer method',
required=True)
parser.add_argument('--explainerUri',
help='The URL of a pretrained explainer',
default=os.environ.get(ENV_STORAGE_URI))
parser.add_argument('--config',
default=os.environ.get(CONFIG_ENV),
help='Custom configuration parameters')
args, _ = parser.parse_known_args()
if __name__ == "__main__":
# Pretrained Alibi explainer
alibi_model = None
if args.explainerUri is not None:
alibi_model = os.path.join(
kfserving.Storage.download(args.explainerUri), EXPLAINER_FILENAME)
with open(alibi_model, 'rb') as f:
alibi_model = dill.load(f)
# Custom configuration
if args.config is None:
config = {}
else:
config = json.loads(args.config)
explainer = AlibiExplainer(args.explainer_name,
args.predict_url, args.protocol,
ExplainerMethod(args.type), config, alibi_model)
explainer.load()
kfserving.KFServer().start(models=[explainer])
import argparse
from alibiexplainer import AlibiExplainer
from alibiexplainer.explainer import ExplainerMethod #pylint:disable=no-name-in-module
DEFAULT_MODEL_NAME = "model"
parser = argparse.ArgumentParser(parents=[kfserving.server.parser]) #pylint:disable=c-extension-no-member
parser.add_argument('--model_name',
default=DEFAULT_MODEL_NAME,
help='The name that the model is served under.')
parser.add_argument('--predict_url',
help='The URL for the model predict function',
required=True)
parser.add_argument('--method',
type=ExplainerMethod,
choices=list(ExplainerMethod),
default="anchor_tabular",
help='Explainer method')
parser.add_argument('--training_data', help='The URL for the training data')
args, _ = parser.parse_known_args()
if __name__ == "__main__":
explainer = AlibiExplainer(args.model_name,
args.predict_url,
args.protocol,
ExplainerMethod(args.method),
training_data_url=args.training_data)
explainer.load()
kfserving.KFServer().start(models=[explainer]) #pylint:disable=c-extension-no-member
type=float,
action=GroupedAction,
dest='explainer.p_sample',
default=argparse.SUPPRESS)
args, _ = parser.parse_known_args()
argdDict = vars(args).copy()
if 'explainer' in argdDict:
extra = vars(args.explainer)
else:
extra = {}
logging.info("Extra args: %s", extra)
if __name__ == "__main__":
# Pretrained Alibi explainer
alibi_model = None
if args.storage_uri is not None:
alibi_model = os.path.join(
kfserving.Storage.download(args.storage_uri), EXPLAINER_FILENAME)
with open(alibi_model, 'rb') as f:
logging.info("Loading Alibi model")
alibi_model = dill.load(f)
explainer = AlibiExplainer(args.model_name,
args.predictor_host, args.protocol,
ExplainerMethod(args.command), extra,
alibi_model)
explainer.load()
kfserving.KFServer().start(models=[explainer])