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dataset / dataset.py

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	# -- coding: utf-8 --
	"""dataset.ipynb

	Automatically generated by Colaboratory.

	Original file is located at
	https://colab.research.google.com/drive/1sNXmgV-J4w6JSdtXK-0TckTP5SFkGPtz

	###Create a file.py
	"""

	import datasets
	import csv
	import pandas as pd

	_URLS = {
	"zh-en": {
	"TRAIN_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1z-reeSB_pAcZEJicRpBJWzrhuwdtJ-d1&export=download",
	"VALIDATION_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1f1izEby8pfXZWG7htvcky_FL2iTMnoD5&export=download",
	"TEST_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1VGM96MZvMuAPJoFzBeSpyC16IDSiu0vC&export=download"
	}
	}

	class NewDataset(datasets.GeneratorBasedBuilder):

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name = "zh-en",
	version = VERSION,
	description = "The translation dataset between Traditional Chinese and English"
	)
	]

	def _info(self):

	if self.config.name == "zh-en": # This is the name of the configuration selected in BUILDER_CONFIGS above
	features = datasets.Features(
	{ "translation": datasets.features.Translation( languages=["en", "zh"] ) }
	)

	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	# description=_DESCRIPTION,
	# This defines the different columns of the dataset and their types
	features=features, # Here we define them above because they are different between the two configurations
	# If there's a common (input, target) tuple from the features,
	# specify them here. They'll be used if as_supervised=True in
	# builder.as_dataset.
	supervised_keys=None,
	# Homepage of the dataset for documentation
	# homepage=_HOMEPAGE,
	# License for the dataset if available
	# license=_LICENSE,
	# Citation for the dataset
	# citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	""" Returns SplitGenerators"""

	my_urls = _URLS[self.config.name]

	train_path = dl_manager.download_and_extract(my_urls["TRAIN_DOWNLOAD_URL"])
	validation_path = dl_manager.download_and_extract(my_urls["VALIDATION_DOWNLOAD_URL"])
	test_path = dl_manager.download_and_extract(my_urls["TEST_DOWNLOAD_URL"])

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs = { "filepath" : train_path, "split" : "train" }
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs = { "filepath" : validation_path, "split" : "validation" }
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs = { "filepath" : test_path, "split" : "test"},
	)
	]

	def _generate_examples(self, filepath, split):
	""" Generate Dravidian MT examples"""

	with open(filepath, encoding="utf-8") as f:
	reader = csv.DictReader(f)
	for idx, row in enumerate(reader):

	if self.config.name == "zh-en":
	result = { "translation" : { "en" : row["en"], "zh" : row["zh"] } }

	yield idx, result