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import json
import os
import datasets
_OPEN_SLU_CITATION = """\
xxx"""
_OPEN_SLU_DESCRIPTION = """\
xxx"""
_ATIS_CITATION = """\
@inproceedings{hemphill1990atis,
title = "The {ATIS} Spoken Language Systems Pilot Corpus",
author = "Hemphill, Charles T. and
Godfrey, John J. and
Doddington, George R.",
booktitle = "Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, {P}ennsylvania, June 24-27,1990",
year = "1990",
url = "https://aclanthology.org/H90-1021",
}
"""
_ATIS_DESCRIPTION = """\
A widely used SLU corpus for single-intent SLU.
"""
class OpenSLUConfig(datasets.BuilderConfig):
"""BuilderConfig for OpenSLU."""
def __init__(self, features, data_url, citation, url, intent_label_classes=None, slot_label_classes=None, **kwargs):
"""BuilderConfig for OpenSLU.
Args:
features: `list[string]`, list of the features that will appear in the
feature dict. Should not include "label".
data_url: `string`, url to download the zip file from.
citation: `string`, citation for the data set.
url: `string`, url for information about the data set.
intent_label_classes: `list[string]`, the list of classes for the intent label
slot_label_classes: `list[string]`, the list of classes for the slot label
**kwargs: keyword arguments forwarded to super.
"""
# Version history:
# 0.0.1: Initial version.
super(OpenSLUConfig, self).__init__(version=datasets.Version("0.0.1"), **kwargs)
self.features = features
self.intent_label_classes = intent_label_classes
self.slot_label_classes = slot_label_classes
self.data_url = data_url
self.citation = citation
self.url = url
class OpenSLU(datasets.GeneratorBasedBuilder):
"""The SuperGLUE benchmark."""
BUILDER_CONFIGS = [
OpenSLUConfig(
name="products",
description=_ATIS_DESCRIPTION,
features=["text"],
data_url="https://huggingface.co/datasets/rams901/OpenSLU_Clone/resolve/main/prods.tar.gz",
citation=_ATIS_CITATION,
url="https://aclanthology.org/H90-1021",
),
]
def _info(self):
features = {feature: datasets.Sequence(datasets.Value("string")) for feature in self.config.features}
features["slot"] = datasets.Sequence(datasets.Value("string"))
features["intent"] = datasets.Value("string")
return datasets.DatasetInfo(
description=_OPEN_SLU_DESCRIPTION + self.config.description,
features=datasets.Features(features),
homepage=self.config.url,
citation=self.config.citation + "\n" + _OPEN_SLU_CITATION,
)
def _split_generators(self, dl_manager):
print(self.config.data_url)
dl_dir = dl_manager.download_and_extract(self.config.data_url) or ""
task_name = _get_task_name_from_data_url(self.config.data_url)
print(dl_dir)
print(task_name)
dl_dir = os.path.join(dl_dir, task_name)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": os.path.join(dl_dir, "train.jsonl"),
"split": datasets.Split.TRAIN,
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"data_file": os.path.join(dl_dir, "dev.jsonl"),
"split": datasets.Split.VALIDATION,
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_file": os.path.join(dl_dir, "test.jsonl"),
"split": datasets.Split.TEST,
},
),
]
def _generate_examples(self, data_file, split):
with open(data_file, encoding="utf-8") as f:
for index, line in enumerate(f):
row = json.loads(line)
yield index, row
def _cast_label(label):
"""Converts the label into the appropriate string version."""
if isinstance(label, str):
return label
elif isinstance(label, bool):
return "True" if label else "False"
elif isinstance(label, int):
assert label in (0, 1)
return str(label)
else:
raise ValueError("Invalid label format.")
def _get_record_entities(passage):
"""Returns the unique set of entities."""
text = passage["text"]
entity_spans = list()
for entity in passage["entities"]:
entity_text = text[entity["start"]: entity["end"] + 1]
entity_spans.append({"text": entity_text, "start": entity["start"], "end": entity["end"] + 1})
entity_spans = sorted(entity_spans, key=lambda e: e["start"]) # sort by start index
entity_texts = set(e["text"] for e in entity_spans) # for backward compatability
return entity_texts, entity_spans
def _get_record_answers(qa):
"""Returns the unique set of answers."""
if "answers" not in qa:
return []
answers = set()
for answer in qa["answers"]:
answers.add(answer["text"])
return sorted(answers)
def _get_task_name_from_data_url(data_url):
return data_url.split("/")[-1].split(".")[0]
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