Delete python script to solve DatasetWithScriptNotSupportedError
#2
by
ivanzhou-uber
- opened
- RedPajama-Tiny.py +0 -103
RedPajama-Tiny.py
DELETED
@@ -1,103 +0,0 @@
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# Copyright 2023 Together Computer
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Lint as: python3
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"""RedPajama: An Open-Source, Clean-Room 1.2 Trillion Token Dataset."""
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import json
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import datasets
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logger = datasets.logging.get_logger(__name__)
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_DESCRIPTION = """\
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RedPajama is a clean-room, fully open-source implementation of the LLaMa dataset. This is a 1B-token sample of the full dataset.
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"""
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_URLS = [
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"arxiv_sample.jsonl",
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"book_sample.jsonl",
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"c4_sample.jsonl",
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"cc_2023-06_sample.jsonl",
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"github_sample.jsonl",
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"stackexchange_sample.jsonl",
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"wikipedia_sample.jsonl",
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]
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class RedPajamaTinyConfig(datasets.BuilderConfig):
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"""BuilderConfig for RedPajama sample."""
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def __init__(self, **kwargs):
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"""BuilderConfig for RedPajama sample.
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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super(RedPajamaTinyConfig, self).__init__(**kwargs)
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class RedPajamaTiny(datasets.GeneratorBasedBuilder):
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"""RedPajama 1T Sample: version 1.0.0."""
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BUILDER_CONFIGS = [
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RedPajamaTinyConfig(
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name="plain_text",
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version=datasets.Version("1.0.0", ""),
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description="Plain text",
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),
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"text": datasets.Value("string"),
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"meta": datasets.Value("string"),
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}
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),
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supervised_keys=None,
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)
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def _split_generators(self, dl_manager):
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downloaded_files = dl_manager.download_and_extract(_URLS)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files})
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]
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def _generate_examples(self, filepaths):
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"""This function returns the examples in the raw (text) form."""
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logger.info("generating examples from = %s", filepaths)
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key = 0
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for filepath in filepaths:
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with open(filepath, encoding="utf-8") as f:
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for row in f:
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data = json.loads(row)
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if "meta" not in data:
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text = data["text"]
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del data["text"]
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yield key, {
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"text": text,
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"meta": json.dumps(data),
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}
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else:
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yield key, {
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"text": data["text"],
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"meta": data["meta"],
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}
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key += 1
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