# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# 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.
# pylint: disable=doc-string-missing
from paddle_serving_client import Client
from paddle_serving_app.reader.imdb_reader import IMDBDataset
import sys
import numpy as np

client = Client()
client.load_client_config(sys.argv[1])
client.add_variant("bow", ["127.0.0.1:9297"], 10)
client.add_variant("cnn", ["127.0.0.1:9298"], 30)
client.add_variant("lstm", ["127.0.0.1:9299"], 60)
client.connect()

# you can define any english sentence or dataset here
# This example reuses imdb reader in training, you
# can define your own data preprocessing easily.
imdb_dataset = IMDBDataset()
imdb_dataset.load_resource(sys.argv[2])

for line in sys.stdin:
    word_ids, label = imdb_dataset.get_words_and_label(line)
    word_len = len(word_ids)
    feed = {
        "words": np.array(word_ids).reshape(word_len, 1),
        "words.lod": [0, word_len]
    }
    #print(feed)
    fetch = ["prediction"]
    fetch_map = client.predict(
        feed=feed, fetch=fetch, batch=True, need_variant_tag=True)
    print("server_tag={} prediction={} ".format(fetch_map[1], fetch_map[0][
        "prediction"][0]))