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GitTables

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GitTables / GitTables.py

yuansui

Update GitTables.py

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	import csv
	import json
	from typing import List
	import jsonlines

	import datasets
	import os

	_CITATION = """\
	@InProceedings{huggingface:dataset,
	title = {A great new dataset},
	author={huggingface, Inc.
	},
	year={2020}
	}
	"""

	_DESCRIPTION = """\
	This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
	"""

	_HOMEPAGE = "https://gittables.github.io/"

	_LICENSE = ""

	# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
	# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
	_URL = "https://huggingface.co/datasets/yuansui/GitTables/resolve/main/" # be attention to the url, use resolve instead of blob
	_URLS = {
	"dbpedia": {
	"train": _URL + "dbpedia" + "_train.jsonl",
	"dev": _URL + "dbpedia" + "_val.jsonl",
	"test": _URL + "dbpedia" + "_test.jsonl",
	},
	"schema": {
	"train": _URL + "schema" + "_train.jsonl",
	"dev": _URL + "schema" + "_val.jsonl",
	"test": _URL + "schema" + "_test.jsonl",
	}
	}


	class GitTablesConfig(datasets.BuilderConfig):
	"""GitTablesConfig for GitTables"""

	def __init__(self, features, data_url, citation, url, label_classes=("False", "True"), **kwargs):
	"""BuilderConfig for SuperGLUE.

	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.
	label_classes: list[string], the list of classes for the label if the
	label is present as a string. Non-string labels will be cast to either
	'False' or 'True'.
	**kwargs: keyword arguments forwarded to super.
	"""
	# Version history:
	# 1.0.1: Fixed non-nondeterminism in ReCoRD.
	super().__init__(version=datasets.Version("1.0.1"), **kwargs)
	self.features = features
	self.label_classes = label_classes
	self.data_url = data_url
	self.citation = citation
	self.url = url


	class GitTables(datasets.GeneratorBasedBuilder):
	"""GitTables benchmark"""
	DEFAULT_CONFIG_NAME = "dbpedia" # It's not mandatory to have a default configuration. Just use one if it make sense.

	BUILDER_CONFIGS = [
	GitTablesConfig(
	name="dbpedia",
	description="Subsets of 1M gittables for column type classification with dbpedia",
	features=["id", "table_id", "target_column", "annotation_id", "annotation_label", "table_text",
	"column_text"],
	data_url=_URLS["dbpedia"],
	citation=_CITATION,
	url=""
	),
	GitTablesConfig(
	name="schema",
	description="Subsets of 1M gittables for column type classification with schema",
	features=["id", "table_id", "target_column", "annotation_id", "annotation_label", "table_text",
	"column_text"],
	data_url=_URLS["schema"],
	citation=_CITATION,
	url=""
	)
	]

	def _info(self):

	features = datasets.Features(
	{
	"id": datasets.Value("int32"),
	"table_id": datasets.Value("string"),
	"target_column": datasets.Value("string"),
	"annotation_id": datasets.Value("string"),
	"annotation_label": datasets.Value("string"),
	"table_text": datasets.Value("string"),
	"column_text": datasets.Value("string")
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features, # Here we define them above because they are different between the two configurations
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
	urls_to_download = _URLS[self.config.name]
	downloaded_files = dl_manager.download_and_extract(urls_to_download)
	# These kwargs will be passed to _generate_examples
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": downloaded_files["train"],
	"split": "train"
	}
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": downloaded_files["dev"],
	"split": "dev"}
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": downloaded_files["test"],
	"split": "test"
	}
	)
	]

	# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
	def _generate_examples(self, filepath, split):
	# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
	with jsonlines.open(filepath, mode="r") as reader:
	for key, row in enumerate(reader):
	data = json.loads(row)
	if self.config.name == "dbpedia":
	table_text = {}
	if data["table_text"] != None:
	print(type(data["table_text"]))
	print(data["table_text"])
	for i in range(35):
	col_info = data["table_text"].get(f"col{i}", "")
	if col_info != "":
	table_text[f"col{i}"] = col_info
	# Yields examples as (key, example) tuples
	yield key, {
	"id": data["id"],
	"table_id": data["table_id"],
	"target_column": data["target_column"],
	"column_text": data["column_text"],
	"annotation_id": data["annotation_id"],
	"annotation_label": data["annotation_label"],
	"table_text": str(table_text)
	}
	else:
	table_text = {}
	for i in range(35):
	col_info = data["table_text"].get(f"col{i}", "")
	if col_info != "":
	table_text[f"col{i}"] = col_info
	yield key, {
	"id": data["id"],
	"table_id": data["table_id"],
	"target_column": data["target_column"],
	"column_text": data["column_text"],
	"annotation_id": data["annotation_id"],
	"annotation_label": data["annotation_label"],
	"table_text": str(table_text),
	}