# Copyright 2017 Neural Networks and Deep Learning lab, MIPT
#
# 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 logging import getLogger
from typing import List, Tuple
from deeppavlov.core.common.registry import register
from deeppavlov.core.models.component import Component
logger = getLogger(__name__)
[docs]@register('top1_elector')
class TopOneElector(Component):
"""Component that chooses a candidate with highest base probability for every token
"""
def __init__(self, *args, **kwargs):
pass
[docs] def __call__(self, batch: List[List[List[Tuple[float, str]]]]) -> List[List[str]]:
"""Choose the best candidate for every token
Args:
batch: batch of probabilities and string values of candidates for every token in a sentence
Returns:
batch of corrected tokenized sentences
"""
return [[max(sublist)[1] for sublist in candidates] for candidates in batch]