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kopi_cc.py

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+# coding=utf-8
+# Copyright 2022 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.
+
+"""
+KoPI-CC corpus
+
+[nusantara_schema_name] = ssp
+"""
+
+import gzip
+import json
+from typing import List
+
+import datasets
+import zstandard as zstd
+
+from nusacrowd.utils import schemas
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import (DEFAULT_NUSANTARA_VIEW_NAME,
+                                       DEFAULT_SOURCE_VIEW_NAME, Tasks)
+
+_DATASETNAME = "kopi_cc"
+_LANGUAGES  = ["ind"]
+_LOCAL = False
+_SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
+_UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
+_URL = "https://commoncrawl.org/"
+_CITATION = """\
+       @ARTICLE{2022arXiv220106642A,
+       author = {{Abadji}, Julien and {Ortiz Suarez}, Pedro and {Romary}, Laurent and {Sagot}, Benoit},
+        title = "{Towards a Cleaner Document-Oriented Multilingual Crawled Corpus}",
+      journal = {arXiv e-prints},
+     keywords = {Computer Science - Computation and Language},
+         year = 2022,
+        month = jan,
+          eid = {arXiv:2201.06642},
+        pages = {arXiv:2201.06642},
+archivePrefix = {arXiv},
+       eprint = {2201.06642},
+ primaryClass = {cs.CL},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2022arXiv220106642A},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+@inproceedings{AbadjiOrtizSuarezRomaryetal.2021,
+  author    = {Julien Abadji and Pedro Javier Ortiz Su{\'a}rez and Laurent Romary and Benoit Sagot},
+  title     = {Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus},
+  series = {Proceedings of the Workshop on Challenges in the Management of Large Corpora (CMLC-9) 2021. Limerick, 12 July 2021 (Online-Event)},
+  editor    = {Harald L{\"u}ngen and Marc Kupietz and Piotr Bański and Adrien Barbaresi and Simon Clematide and Ines Pisetta},
+  publisher = {Leibniz-Institut f{\"u}r Deutsche Sprache},
+  address   = {Mannheim},
+  doi       = {10.14618/ids-pub-10468},
+  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-104688},
+  pages     = {1 -- 9},
+  year      = {2021},
+  abstract  = {Since the introduction of large language models in Natural Language Processing, large raw corpora have played a crucial role in Computational Linguistics.},
+  language  = {en}
+}
+
+"""
+
+_DESCRIPTION = """\
+    KoPI-CC (Korpus Perayapan Indonesia)-CC is Indonesian Only Extract from Common Crawl snapshots ,each snapshots get extracted using ungoliant and get extra "filtering" using deduplication technique
+
+"""
+
+_HOMEPAGE = "https://huggingface.co/datasets/munggok/KoPI-CC"
+
+_LICENSE = "CC0"
+
+_URLS = {
+    "raw": "https://huggingface.co/datasets/munggok/KoPI-CC/resolve/main/{snapshot}/raw/id_meta_{index}.jsonl.zst",
+    "dedup": "https://huggingface.co/datasets/munggok/KoPI-CC/resolve/main/{snapshot}/dedup/oscar-{index:012d}.json.gz",
+    "neardup": "https://huggingface.co/datasets/munggok/KoPI-CC/resolve/main/{snapshot}/neardup/oscar-neardup-{index:012d}.json.gz",
+    "neardup_clean": "https://huggingface.co/datasets/munggok/KoPI-CC/resolve/main/{snapshot}/neardup_clean/cleaned_oscar-neardup-{index:012d}.json.gz",
+}
+
+
+_N_SHARDS_PER_SNAPSHOT = {
+    "2021_10": {"dedup": 132, "neardup": 120, "neardup_clean": 120},
+    "2021_17": {"raw": 31, "dedup": 47, "neardup": 41, "neardup_clean": 41},
+    "2021_21": {"raw": 63, "dedup": 37, "neardup": 33, "neardup_clean": 33},
+    "2021_25": {"raw": 31, "dedup": 32, "neardup": 28, "neardup_clean": 28},
+    "2021_31": {"raw": 35, "dedup": 47, "neardup": 42, "neardup_clean": 42},
+    "2021_39": {"raw": 35, "dedup": 44, "neardup": 38, "neardup_clean": 38},
+    "2021_43": {"raw": 35, "dedup": 44, "neardup": 39, "neardup_clean": 39},
+    "2021_49": {"dedup": 31, "neardup": 28, "neardup_clean": 28},
+    "2022_05": {"raw": 40, "dedup": 18, "neardup": 18, "neardup_clean": 35},
+    "2022_21": {"raw": 40, "dedup": 42, "neardup": 37, "neardup_clean": 37},
+    "2022_27": {"raw": 79, "dedup": 38, "neardup": 33, "neardup_clean": 33},
+}
+
+_SNAP_CONFIG = []
+for m in list(_N_SHARDS_PER_SNAPSHOT.keys()):
+    ka = list(_N_SHARDS_PER_SNAPSHOT[m].keys())
+    conf = [m + "-" + a for a in ka]
+    _SNAP_CONFIG.extend(conf)
+_SUPPORTED_TASKS = [Tasks.SELF_SUPERVISED_PRETRAINING]
+
+_ALL_CONFIG = ["all-raw", "all-dedup", "all-neardup", "all-neardup_clean"] + _SNAP_CONFIG
+
+_SOURCE_VERSION = "2018.12.01"
+
+_NUSANTARA_VERSION = "1.0.0"
+
+
+def nusantara_config_constructor(snapshot, schema, version):
+    """Construct NusantaraConfig"""
+    if schema != "source" and schema != "nusantara_ssp":
+        raise ValueError(f"Invalid schema: {schema}")
+
+    if snapshot == "":
+        raise ValueError(f"Snapshot is required. Choose one of these Snapshot: {_ALL_CONFIG}.")
+    elif snapshot in _SNAP_CONFIG + _ALL_CONFIG:
+        return NusantaraConfig(
+            name=f"{_DATASETNAME}_{snapshot}_{schema}",
+            version=datasets.Version(version),
+            description=f"KoPI-CC with {schema} schema for {snapshot}",
+            schema=schema,
+            subset_id="kopi_cc",
+        )
+    else:
+        raise ValueError(f"Invalid language: {snapshot}. Choose one of these snapshots: {_ALL_CONFIG}.")
+
+
+class KoPICC(datasets.GeneratorBasedBuilder):
+
+    DEFAULT_CONFIG_NAME = "2021_17_dedup"
+
+    BUILDER_CONFIGS = [nusantara_config_constructor(sn, "source", _SOURCE_VERSION) for sn in _ALL_CONFIG] + [nusantara_config_constructor(sn, "nusantara_ssp", _NUSANTARA_VERSION) for sn in _ALL_CONFIG]
+
+    def _info(self):
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "timestamp": datasets.Value("string"),
+                    "url": datasets.Value("string"),
+                    "meta": datasets.Value("string"),
+                }
+            )
+        elif self.config.schema == "nusantara_ssp":
+            features = schemas.self_supervised_pretraining.features
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager) -> List[datasets.SplitGenerator]:
+        """Returns SplitGenerators."""
+        name = self.config.name.replace("_" + self.config.schema, "")
+        name = name.replace(_DATASETNAME + "_", "")
+        split_name = name.split("-")
+        if split_name[0] == "all":
+            urls = []
+            keys = list(_N_SHARDS_PER_SNAPSHOT.keys())
+            idx = 0
+            if split_name[1] == "raw":
+                idx = 1
+                keys = [ur for ur in list(_N_SHARDS_PER_SNAPSHOT.keys()) if _N_SHARDS_PER_SNAPSHOT[ur].get("raw") is not None]
+            for m in keys:
+                urls.extend([_URLS[split_name[1]].format(snapshot=m, index=k + idx) for k in range(_N_SHARDS_PER_SNAPSHOT[m].get(split_name[1]))])
+        else:
+            urls = [_URLS[split_name[1]].format(snapshot=split_name[0], index=k + 1) for k in range(_N_SHARDS_PER_SNAPSHOT[split_name[0]][split_name[1]])]
+        path = dl_manager.download(urls)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepaths": path, "split": "train", "type": split_name[1]},
+            ),
+        ]
+
+    def _generate_examples(self, filepaths, split, type):
+        """This function returns the examples in the raw (text) form by iterating on all the files."""
+        id_ = 0
+        for filepath in filepaths:
+            if type == "raw":
+                with zstd.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
+                    for line in f:
+                        if line:
+                            example = json.loads(line)
+                            meta = dict()
+                            meta["warc_headers"] = example["warc_headers"]
+                            meta["warc_headers"]["warc-identified-content-language"] = example["warc_headers"].get("warc-identified-content-language")
+                            meta["identification"] = example["metadata"]["identification"]
+                            meta["annotations"] = example["metadata"]["annotation"]
+                            meta["line_identifications"] = example["metadata"]["sentence_identifications"]
+                            if self.config.schema == "nusantara_ssp":
+                                yield id_, {"id": str(id_), "text": example["content"]}
+                                id_ += 1
+                            else:
+                                yield id_, {"text": example["content"], "url": example["warc_headers"]["warc-target-uri"], "timestamp": example["warc_headers"]["warc-date"], "meta": json.dumps(meta)}
+                                id_ += 1
+            else:
+                with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
+                    for line in f:
+                        if line:
+                            example = json.loads(line)
+                            if self.config.schema == "nusantara_ssp":
+                                yield id_, {"id": str(id_), "text": example["text"]}
+                                id_ += 1
+                            else:
+                                yield id_, {"text": example["text"], "url": example["url"], "timestamp": example["timestamp"], "meta": example["meta"]}
+                                id_ += 1