Source code for deeppavlov.dataset_iterators.dstc2_intents_iterator

# 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
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.

from logging import getLogger
from typing import List

from deeppavlov.core.common.registry import register
from deeppavlov.dataset_iterators.basic_classification_iterator import BasicClassificationDatasetIterator

log = getLogger(__name__)

[docs]@register('dstc2_intents_iterator') class Dstc2IntentsDatasetIterator(BasicClassificationDatasetIterator): """ Class gets data dictionary from DSTC2DatasetReader instance, construct intents from act and slots, \ merge fields if necessary, split a field if necessary Args: data: dictionary of data with fields "train", "valid" and "test" (or some of them) fields_to_merge: list of fields (out of ``"train", "valid", "test"``) to merge merged_field: name of field (out of ``"train", "valid", "test"``) to which save merged fields field_to_split: name of field (out of ``"train", "valid", "test"``) to split split_fields: list of fields (out of ``"train", "valid", "test"``) to which save splitted field split_proportions: list of corresponding proportions for splitting seed: random seed shuffle: whether to shuffle examples in batches *args: arguments **kwargs: arguments Attributes: data: dictionary of data with fields "train", "valid" and "test" (or some of them) """ def __init__(self, data: dict, fields_to_merge: List[str] = None, merged_field: str = None, field_to_split: str = None, split_fields: List[str] = None, split_proportions: List[float] = None, seed: int = None, shuffle: bool = True, *args, **kwargs): """ Initialize dataset using data from DatasetReader, merges and splits fields according to the given parameters """ super().__init__(data, fields_to_merge, merged_field, field_to_split, split_fields, split_proportions, seed=seed, shuffle=shuffle) new_data = dict() new_data['train'] = [] new_data['valid'] = [] new_data['test'] = [] for field in ['train', 'valid', 'test']: for turn in[field]: reply = turn[0] curr_intents = [] if reply['intents']: for intent in reply['intents']: for slot in intent['slots']: if slot[0] == 'slot': curr_intents.append(intent['act'] + '_' + slot[1]) else: curr_intents.append(intent['act'] + '_' + slot[0]) if len(intent['slots']) == 0: curr_intents.append(intent['act']) else: if reply['text']: curr_intents.append('unknown') else: continue new_data[field].append((reply['text'], curr_intents)) = new_data