kserve/python/aiffairness/aifserver/__main__.py

# Copyright 2021 The KServe Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse

import kserve
import json

from kserve import logging
from .model import AIFModel

DEFAULT_MODEL_NAME = "aifserver"

parser = argparse.ArgumentParser(parents=[kserve.model_server.parser])

parser.add_argument(
    "--model_name",
    default=DEFAULT_MODEL_NAME,
    help="The name that the model is served under.",
)

parser.add_argument(
    "--predictor_host", help="The host for the predictor.", required=True
)

# Parameters for describing the model being used for aif360
# ie. feature / label names,
# Arguments with nargs='+' take a list of 1 or more
# ie '... --feature_names age sex credit_history ...'
parser.add_argument("--feature_names", nargs="+", required=True)

parser.add_argument("--label_names", nargs="+", required=True)

parser.add_argument("--favorable_label", type=float, required=True)

parser.add_argument("--unfavorable_label", type=float, required=True)

# type=json.loads parses the string from json to a python dict
parser.add_argument(
    "--privileged_groups",
    type=json.loads,
    help="Privileged groups.",
    nargs="+",
    required=True,
)

parser.add_argument(
    "--unprivileged_groups",
    help="Unprivileged groups.",
    type=json.loads,
    nargs="+",
    required=True,
)

args, _ = parser.parse_known_args()

if __name__ == "__main__":
    if args.configure_logging:
        logging.configure_logging(args.log_config_file)
    model = AIFModel(
        name=args.model_name,
        feature_names=args.feature_names,
        label_names=args.label_names,
        favorable_label=args.favorable_label,
        unfavorable_label=args.unfavorable_label,
        privileged_groups=args.privileged_groups,
        unprivileged_groups=args.unprivileged_groups,
    )
    model.load()
    kserve.ModelServer().start([model])