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# coding=utf-8
# Copyright 2023 The HuggingFace Datasets Authors and Ilya Gusev
#
# 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.
# Lint as: python3
"""RuLM: a dataset for Russian language modeling"""
import os
import io
import zstandard
import jsonlines
import datasets
try:
import simdjson
parser = simdjson.Parser()
def parse_json(x):
try:
return parser.parse(x).as_dict()
except ValueError:
return
except ImportError:
import json
def parse_json(x):
return json.loads(x)
_TRAIN_SPLITS = 20
_DESCRIPTION = "Dataset for Russian language modeling"
_URLS = {
"train": ["train/{}.jsonl.zst".format(str(i).zfill(2)) for i in range(_TRAIN_SPLITS)],
"validation": "validation.jsonl.zst",
"test": "test.jsonl.zst"
}
_TEXT = "text"
class RuLMDataset(datasets.GeneratorBasedBuilder):
"""RuLM Dataset"""
VERSION = datasets.Version("0.0.1")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="default", version=VERSION, description=""),
]
DEFAULT_CONFIG_NAME = "default"
def _info(self):
features = datasets.Features(
{
"text": datasets.Value("string"),
"meta": {
"source": datasets.Value("string"),
"url": datasets.Value("string")
}
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=(_TEXT,)
)
def _split_generators(self, dl_manager):
downloaded_files = dl_manager.download(_URLS)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"paths": downloaded_files["train"]}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"paths": downloaded_files["test"]}),
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"paths": downloaded_files["validation"]}),
]
def _generate_examples(self, paths):
if not isinstance(paths, list):
paths = [paths]
for filename in paths:
with open(filename, "rb") as f:
cctx = zstandard.ZstdDecompressor()
reader_stream = io.BufferedReader(cctx.stream_reader(f))
reader = jsonlines.Reader(reader_stream, loads=parse_json)
for id_, item in enumerate(reader):
yield id_, item
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