"""
/**
* Copyright 2020 Tianshu AI Platform. 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.
* =============================================================
*/
"""
from entrance.executor import classify_by_textcnn as classify


def _init():
    print('init classify_obj')
    global classify_obj
    classify_obj = classify.TextCNNClassifier()  # label_log


def _classification(text_path_list, id_list, label_list):
    """Perform automatic text classification task."""
    textnum = len(text_path_list)
    batched_num = ((textnum - 1) // classify.BATCH_SIZE + 1) * classify.BATCH_SIZE
    for i in range(batched_num - textnum):
        text_path_list.append(text_path_list[0])
        id_list.append(id_list[0])
    annotations = classify_obj.inference(text_path_list, id_list, label_list)  #
    return annotations[0:textnum]


if __name__ == "__main__":
    test_len = 22
    _init()
    ans = _classification(["dubhe-dev/dataset/2738/origin/32_3_ts1607326726114630.txt"] * test_len, [1] * test_len,
                          [111, 112])
    print(ans)
    print(len(ans))