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import json |
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from pathlib import Path |
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from typing import Dict, List, Tuple |
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import datasets |
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from seacrowd.utils import schemas |
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from seacrowd.utils.configs import SEACrowdConfig |
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from seacrowd.utils.constants import Tasks, Licenses |
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_CITATION = """\ |
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@article{kautsar2023indotod, |
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author={Kautsar, Muhammad Dehan Al and Nurdini, Rahmah Khoirussyifa' and Cahyawijaya, Samuel and Winata, Genta Indra and Purwarianti, Ayu}, |
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title={IndoToD: A Multi-Domain Indonesian Benchmark For End-to-End Task-Oriented Dialogue Systems}, |
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journal={arXiv preprint arXiv:2311.00958}, |
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year={2023}, |
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} |
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""" |
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_LANGUAGES = ["ind"] |
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_LOCAL = False |
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_DATASETNAME = "indosmd" |
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_DESCRIPTION = """\ |
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IndoSMD is a synthetic task-oriented dialogue system dataset that was translated from the In-Car Assistant (SMD) dataset (Eric et al., 2017) into the new Indonesian dataset using the translation pipeline method |
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including delexicalization, translation, and delexicalization. The dataset consists of 323 dialogues in the POI Navigation, Calendar Scheduling, and Weather Information Retrieval domain, with a user and an agent talking to each other. |
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It also consists of slots and dialogue acts from the user and the agent. |
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""" |
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_HOMEPAGE = "https://github.com/dehanalkautsar/IndoToD/tree/main/IndoSMD" |
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_LICENSE = Licenses.CC_BY_SA_4_0.value |
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_URLS = { |
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_DATASETNAME: { |
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"train": "https://raw.githubusercontent.com/dehanalkautsar/IndoToD/main/IndoSMD/IndoSMD_split/IndoSMD_train.json", |
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"validation": "https://raw.githubusercontent.com/dehanalkautsar/IndoToD/main/IndoSMD/IndoSMD_split/IndoSMD_dev.json", |
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"test": "https://raw.githubusercontent.com/dehanalkautsar/IndoToD/main/IndoSMD/IndoSMD_split/IndoSMD_test.json", |
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}, |
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} |
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_SUPPORTED_TASKS = [Tasks.E2E_TASK_ORIENTED_DIALOGUE] |
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_SOURCE_VERSION = "1.0.0" |
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_SEACROWD_VERSION = "2024.06.20" |
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class IndoSMDDataset(datasets.GeneratorBasedBuilder): |
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"""IndoToD: A Multi-Domain Indonesian Benchmark For End-to-End Task-Oriented Dialogue Systems""" |
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) |
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SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION) |
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BUILDER_CONFIGS = [ |
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SEACrowdConfig( |
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name=f"{_DATASETNAME}_source", |
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version=SOURCE_VERSION, |
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description="IndoToD: IndoSMD source schema", |
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schema="source", |
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subset_id=f"{_DATASETNAME}", |
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), |
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SEACrowdConfig( |
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name=f"{_DATASETNAME}_seacrowd_tod", |
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version=SEACROWD_VERSION, |
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description="IndoToD: IndoSMD SEACrowd End-to-end Task Oriented Dialogue schema", |
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schema="seacrowd_tod", |
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subset_id=f"{_DATASETNAME}", |
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), |
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] |
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DEFAULT_CONFIG_NAME = "indosmd_source" |
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def _info(self) -> datasets.DatasetInfo: |
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if self.config.schema == "source": |
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features = datasets.Features( |
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{ |
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"index": datasets.Value("string"), |
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"dialogue": [ |
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{ |
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"turn": datasets.Value("string"), |
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"data": { |
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"end_dialogue": datasets.Value("string"), |
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"utterance": datasets.Value("string"), |
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"delex_utterance": datasets.Value("string"), |
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"requested": { |
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"distance": datasets.Value("string"), |
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"traffic_info": datasets.Value("string"), |
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"poi_type": datasets.Value("string"), |
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"address": datasets.Value("string"), |
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"poi": datasets.Value("string"), |
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"room": datasets.Value("string"), |
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"agenda": datasets.Value("string"), |
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"time": datasets.Value("string"), |
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"date": datasets.Value("string"), |
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"party": datasets.Value("string"), |
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"event": datasets.Value("string"), |
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"weather_attribute": datasets.Value("string"), |
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"location": datasets.Value("string"), |
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}, |
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"slots": { |
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"distance": datasets.Value("string"), |
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"traffic_info": datasets.Value("string"), |
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"poi_type": datasets.Value("string"), |
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"address": datasets.Value("string"), |
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"poi": datasets.Value("string"), |
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"room": datasets.Value("string"), |
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"agenda": datasets.Value("string"), |
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"time": datasets.Value("string"), |
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"date": datasets.Value("string"), |
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"party": datasets.Value("string"), |
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"event": datasets.Value("string"), |
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"weather_attribute": datasets.Value("string"), |
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"location": datasets.Value("string"), |
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}, |
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}, |
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} |
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], |
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"scenario": { |
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"kb": { |
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"items": [ |
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{ |
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"distance": datasets.Value("string"), |
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"traffic_info": datasets.Value("string"), |
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"poi_type": datasets.Value("string"), |
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"address": datasets.Value("string"), |
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"poi": datasets.Value("string"), |
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"room": datasets.Value("string"), |
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"agenda": datasets.Value("string"), |
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"time": datasets.Value("string"), |
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"date": datasets.Value("string"), |
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"party": datasets.Value("string"), |
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"event": datasets.Value("string"), |
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"monday": datasets.Value("string"), |
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"tuesday": datasets.Value("string"), |
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"wednesday": datasets.Value("string"), |
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"thursday": datasets.Value("string"), |
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"friday": datasets.Value("string"), |
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"saturday": datasets.Value("string"), |
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"sunday": datasets.Value("string"), |
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"today": datasets.Value("string"), |
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"location": datasets.Value("string"), |
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} |
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], |
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"column_names": [datasets.Value("string")], |
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"kb_title": datasets.Value("string"), |
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}, |
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"task": {"intent": datasets.Value("string")}, |
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"uuid": datasets.Value("string"), |
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}, |
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} |
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) |
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elif self.config.schema == "seacrowd_tod": |
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features = schemas.tod_features |
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else: |
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raise NotImplementedError(f"Schema {self.config.schema} has not been implemented") |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
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"""Returns SplitGenerators.""" |
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urls = _URLS[_DATASETNAME] |
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data_dir = dl_manager.download_and_extract(urls) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": data_dir["train"], |
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"split": "train", |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"filepath": data_dir["validation"], |
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"split": "validation", |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"filepath": data_dir["test"], |
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"split": "test", |
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}, |
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), |
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] |
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def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]: |
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"""Yields examples as (key, example) tuples.""" |
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key_slot_constant = ["distance", "traffic_info", "poi_type", "address", "poi", "room", "agenda", "time", "date", "party", "event", "weather_attribute", "location"] |
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key_kb_constant = ["distance", "traffic_info", "poi_type", "address", "poi", "room", "agenda", "time", "date", "party", "event", "monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday", "today", "location"] |
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with open(filepath, "r+") as fw: |
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data = json.loads(fw.read()) |
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if self.config.schema == "source": |
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for idx, example in enumerate(data): |
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example["index"] = str(idx) |
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for i in range(len(example["dialogue"])): |
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if "requested" not in example["dialogue"][i]["data"]: |
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example["dialogue"][i]["data"]["requested"] = {} |
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example["dialogue"][i]["data"]["slots"] = {} |
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for key in key_slot_constant: |
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example["dialogue"][i]["data"]["requested"][key] = "" |
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example["dialogue"][i]["data"]["slots"][key] = "" |
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else: |
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for key in key_slot_constant: |
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if key not in example["dialogue"][i]["data"]["requested"]: |
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example["dialogue"][i]["data"]["requested"][key] = "" |
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if key not in example["dialogue"][i]["data"]["slots"]: |
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example["dialogue"][i]["data"]["slots"][key] = "" |
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if not example["scenario"]["kb"].get("items"): |
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example["scenario"]["kb"]["items"] = [] |
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for i in range(len(example["scenario"]["kb"]["items"])): |
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for key in key_kb_constant: |
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if key not in example["scenario"]["kb"]["items"][i]: |
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example["scenario"]["kb"]["items"][i][key] = "" |
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yield str(idx), example |
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elif self.config.schema == "seacrowd_tod": |
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for idx, tod_dialogue in enumerate(data): |
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example = {} |
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example["dialogue_idx"] = idx |
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dialogue = [] |
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for turn, i in enumerate(range(0, len(tod_dialogue["dialogue"]) + 2, 2)): |
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dial = {} |
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dial["turn_idx"] = turn |
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dial["system_utterance"] = "" |
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dial["system_acts"] = [] |
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if turn != 0: |
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dial["system_utterance"] = tod_dialogue["dialogue"][i - 1]["data"]["utterance"] |
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if i < len(tod_dialogue["dialogue"]): |
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for act in tod_dialogue["dialogue"][i + 1]["data"]["requested"]: |
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if tod_dialogue["dialogue"][i + 1]["data"]["requested"][act]: |
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dial["system_acts"].append([act]) |
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dial["turn_label"] = [] |
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dial["belief_state"] = [] |
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if i == len(tod_dialogue["dialogue"]): |
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dial["user_utterance"] = "" |
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else: |
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dial["user_utterance"] = tod_dialogue["dialogue"][i]["data"]["utterance"] |
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for act in tod_dialogue["dialogue"][i + 1]["data"]["requested"]: |
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if tod_dialogue["dialogue"][i + 1]["data"]["requested"][act]: |
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dial["belief_state"].append({"slots": [["slot", act]], "act": "request"}) |
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for slot, slot_value in tod_dialogue["dialogue"][i + 1]["data"]["slots"].items(): |
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dial["belief_state"].append({"slots": [[slot, slot_value]], "act": "inform"}) |
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dialogue.append(dial) |
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example["dialogue"] = dialogue |
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yield str(idx), example |
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