Datasets:
Tasks:
Question Answering
Modalities:
Text
Sub-tasks:
extractive-qa
Languages:
English
Size:
1M<n<10M
"""Causal QA : """ | |
import os | |
import sys | |
import json | |
import csv | |
import yaml | |
import urllib3 | |
import datasets | |
class CausalqaConfig(datasets.BuilderConfig): | |
"""BuilderConfig for causalqa.""" | |
def __init__( | |
self, | |
data_features, | |
data_url, | |
citation, | |
**kwargs | |
): | |
"""BuilderConfig for GLUE. | |
Args: | |
data_features: `dict[string, string]`, map from the name of the feature | |
dict for each text field to the name of the column in the tsv file | |
data_url: `dict[string, string]`, url to download the zip file from | |
citation: `string`, citation for the data set | |
process_label: `Function[string, any]`, function taking in the raw value | |
of the label and processing it to the form required by the label feature | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(CausalqaConfig, self).__init__(**kwargs) | |
self.data_features = data_features | |
self.data_url = data_url | |
self.citation = citation | |
def OneBuild(data_info, feat_meta): | |
main_name = [*data_info][0] | |
submain_name = data_info[main_name].keys() | |
all_config = [] | |
for k in submain_name: | |
fm_temp = feat_meta[main_name][k] | |
one_data_info = data_info[main_name][k] | |
cqa_config = CausalqaConfig( | |
name="{}.{}".format(main_name,k), | |
description=one_data_info["description"], | |
version=datasets.Version(one_data_info["version"], ""), | |
data_features=fm_temp, | |
data_url=one_data_info["url_data"], | |
citation=one_data_info["citation"] | |
) | |
all_config.append(cqa_config) | |
return all_config | |
class CausalQA(datasets.GeneratorBasedBuilder): | |
"""CausalQA: An QA causal type dataset.""" | |
http = urllib3.PoolManager() | |
_PATH_METADATA_RES = http.request('GET', 'https://huggingface.co/datasets/jakartaresearch/causalqa/raw/main/source/features_metadata.yaml') | |
_FILE_URL_RES = http.request('GET', 'https://huggingface.co/datasets/jakartaresearch/causalqa/raw/main/source/dataset_info.json') | |
_FILE_URL = json.loads(_FILE_URL_RES.data.decode("utf-8")) | |
_PATH_DESCRIPTION_RES = http.request('GET', 'https://huggingface.co/datasets/jakartaresearch/causalqa/raw/main/source/dataset_description.txt') | |
_CAUSALQA_DESCRIPTION = _PATH_DESCRIPTION_RES.data.decode("utf-8") | |
_HOMEPAGE = _FILE_URL['homepage'] | |
all_files = _FILE_URL['files'] | |
try: | |
fmeta = yaml.safe_load(_PATH_METADATA_RES.data) | |
except yaml.YAMLError as exc: | |
print(exc) | |
BUILDER_CONFIGS = [] | |
for f in all_files: | |
BUILDER_CONFIGS += (OneBuild(f, fmeta)) | |
def _info(self): | |
self.features = {feat: datasets.Value(self.config.data_features[feat]) | |
for feat in self.config.data_features} | |
return datasets.DatasetInfo( | |
description=self._CAUSALQA_DESCRIPTION, | |
features=datasets.Features(self.features), | |
homepage=self._HOMEPAGE | |
) | |
def _split_generators(self, dl_manager): | |
data_train = dl_manager.download(self.config.data_url['train']) | |
data_val = dl_manager.download(self.config.data_url['val']) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"filepath": data_train | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={ | |
"filepath": data_val ## keys (as parameters) is used during generate example | |
}, | |
) | |
] | |
def _generate_examples(self, filepath): | |
"""Generate examples.""" | |
csv.field_size_limit(1000000000) | |
with open(filepath, encoding="utf-8") as csv_file: | |
csv_reader = csv.reader(csv_file, delimiter=",") | |
next(csv_reader) | |
## the yield depends on files features | |
for id_, row in enumerate(csv_reader): | |
existing_values = row | |
feature_names = [*self.features] | |
one_example_row = dict(zip(feature_names, existing_values)) | |
yield id_, one_example_row | |