chr_en / chr_en.py
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# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""ChrEn: Cherokee-English Machine Translation data"""
import openpyxl # noqa: requires this pandas optional dependency for reading xlsx files
import pandas as pd
import datasets
_CITATION = """\
@inproceedings{zhang2020chren,
title={ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization},
author={Zhang, Shiyue and Frey, Benjamin and Bansal, Mohit},
booktitle={EMNLP2020},
year={2020}
}
"""
_DESCRIPTION = """\
ChrEn is a Cherokee-English parallel dataset to facilitate machine translation research between Cherokee and English.
ChrEn is extremely low-resource contains 14k sentence pairs in total, split in ways that facilitate both in-domain and out-of-domain evaluation.
ChrEn also contains 5k Cherokee monolingual data to enable semi-supervised learning.
"""
_HOMEPAGE = "https://github.com/ZhangShiyue/ChrEn"
_LICENSE = ""
_URLs = {
"monolingual_raw": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/raw/monolingual_data.xlsx",
"parallel_raw": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/raw/parallel_data.xlsx",
"monolingual_chr": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/chr",
"monolingual_en5000": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/en5000",
"monolingual_en10000": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/en10000",
"monolingual_en20000": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/en20000",
"monolingual_en50000": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/en50000",
"monolingual_en100000": "https://raw.githubusercontent.com/ZhangShiyue/ChrEn/main/data/monolingual/en100000",
"parallel_train.chr": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/train.chr",
"parallel_train.en": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/train.en",
"parallel_dev.chr": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/dev.chr",
"parallel_dev.en": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/dev.en",
"parallel_out_dev.chr": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/out_dev.chr",
"parallel_out_dev.en": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/out_dev.en",
"parallel_test.chr": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/test.chr",
"parallel_test.en": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/test.en",
"parallel_out_test.chr": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/out_test.chr",
"parallel_out_test.en": "https://github.com/ZhangShiyue/ChrEn/raw/main/data/parallel/out_test.en",
}
# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
class ChrEn(datasets.GeneratorBasedBuilder):
"""ChrEn: Cherokee-English Machine Translation data."""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="monolingual_raw", version=VERSION, description="Monolingual data with metadata"),
datasets.BuilderConfig(name="parallel_raw", version=VERSION, description="Parallel data with metadata"),
datasets.BuilderConfig(name="monolingual", version=VERSION, description="Monolingual data text only"),
datasets.BuilderConfig(
name="parallel", version=VERSION, description="Parallel data text pairs only with default split"
),
]
DEFAULT_CONFIG_NAME = (
"parallel" # It's not mandatory to have a default configuration. Just use one if it make sense.
)
def _info(self):
if (
self.config.name == "monolingual_raw"
): # This is the name of the configuration selected in BUILDER_CONFIGS above
features = datasets.Features(
{
"text_sentence": datasets.Value("string"),
"text_title": datasets.Value("string"),
"speaker": datasets.Value("string"),
"date": datasets.Value("int32"),
"type": datasets.Value("string"),
"dialect": datasets.Value("string"),
}
)
elif (
self.config.name == "parallel_raw"
): # This is the name of the configuration selected in BUILDER_CONFIGS above
features = datasets.Features(
{
"line_number": datasets.Value("string"), # doesn't always map to a number
"sentence_pair": datasets.Translation(languages=["en", "chr"]),
"text_title": datasets.Value("string"),
"speaker": datasets.Value("string"),
"date": datasets.Value("int32"),
"type": datasets.Value("string"),
"dialect": datasets.Value("string"),
}
)
elif (
self.config.name == "parallel"
): # This is an example to show how to have different features for "first_domain" and "second_domain"
features = datasets.Features(
{
"sentence_pair": datasets.Translation(languages=["en", "chr"]),
}
)
elif (
self.config.name == "monolingual"
): # This is an example to show how to have different features for "first_domain" and "second_domain"
features = datasets.Features(
{
"sentence": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features, # Here we define them above because they are different between the two configurations
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
data_dir = dl_manager.download(_URLs)
if self.config.name in [
"monolingual_raw",
"parallel_raw",
]: # This is the name of the configuration selected in BUILDER_CONFIGS above
return [
datasets.SplitGenerator(
name="full",
gen_kwargs={
"filepaths": data_dir,
"split": "full",
},
)
]
elif self.config.name == "monolingual":
return [
datasets.SplitGenerator(
name=spl,
gen_kwargs={
"filepaths": data_dir,
"split": spl,
},
)
for spl in ["chr", "en5000", "en10000", "en20000", "en50000", "en100000"]
]
else:
return [
datasets.SplitGenerator(
name=spl,
gen_kwargs={
"filepaths": data_dir,
"split": spl,
},
)
for spl in ["train", "dev", "out_dev", "test", "out_test"]
]
def _generate_examples(self, filepaths, split):
if self.config.name == "monolingual_raw":
keys = ["text_sentence", "text_title", "speaker", "date", "type", "dialect"]
with open(filepaths["monolingual_raw"], "rb") as f:
monolingual = pd.read_excel(f, engine="openpyxl")
for id_, row in enumerate(monolingual.itertuples()):
yield id_, dict(zip(keys, row[1:]))
elif self.config.name == "parallel_raw":
keys = ["line_number", "en_sent", "chr_sent", "text_title", "speaker", "date", "type", "dialect"]
with open(filepaths["parallel_raw"], "rb") as f:
parallel = pd.read_excel(f, engine="openpyxl")
for id_, row in enumerate(parallel.itertuples()):
res = dict(zip(keys, row[1:]))
res["sentence_pair"] = {"en": res["en_sent"], "chr": res["chr_sent"]}
res["line_number"] = str(res["line_number"])
del res["en_sent"]
del res["chr_sent"]
yield id_, res
elif self.config.name == "monolingual":
f = open(filepaths[f"monolingual_{split}"], encoding="utf-8")
for id_, line in enumerate(f):
yield id_, {"sentence": line.strip()}
elif self.config.name == "parallel":
fi = open(filepaths[f"parallel_{split}.en"], encoding="utf-8")
fo = open(filepaths[f"parallel_{split}.chr"], encoding="utf-8")
for id_, (line_en, line_chr) in enumerate(zip(fi, fo)):
yield id_, {"sentence_pair": {"en": line_en.strip(), "chr": line_chr.strip()}}