vqa_re_convert.py

# copyright (c) 2022 PaddlePaddle Authors. All Rights Reserve.
#
# 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 numpy as np


class TensorizeEntitiesRelations(object):
    def __init__(self, max_seq_len=512, infer_mode=False, **kwargs):
        self.max_seq_len = max_seq_len
        self.infer_mode = infer_mode

    def __call__(self, data):
        entities = data['entities']
        relations = data['relations']

        entities_new = np.full(
            shape=[self.max_seq_len + 1, 3], fill_value=-1, dtype='int64')
        entities_new[0, 0] = len(entities['start'])
        entities_new[0, 1] = len(entities['end'])
        entities_new[0, 2] = len(entities['label'])
        entities_new[1:len(entities['start']) + 1, 0] = np.array(entities[
            'start'])
        entities_new[1:len(entities['end']) + 1, 1] = np.array(entities['end'])
        entities_new[1:len(entities['label']) + 1, 2] = np.array(entities[
            'label'])

        relations_new = np.full(
            shape=[self.max_seq_len * self.max_seq_len + 1, 2],
            fill_value=-1,
            dtype='int64')
        relations_new[0, 0] = len(relations['head'])
        relations_new[0, 1] = len(relations['tail'])
        relations_new[1:len(relations['head']) + 1, 0] = np.array(relations[
            'head'])
        relations_new[1:len(relations['tail']) + 1, 1] = np.array(relations[
            'tail'])

        data['entities'] = entities_new
        data['relations'] = relations_new
        return data