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kopi_nllb.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.
+"""KoPI-NLLB corpus."""
+import json
+
+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)
+
+logger = datasets.logging.get_logger(__name__)
+
+_CITATION = """
+
+Hefferman et al, Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages. Arxiv https://arxiv.org/abs/2205.12654, 2022.
+NLLB Team et al, No Language Left Behind: Scaling Human-Centered Machine Translation, Arxiv https://arxiv.org/abs/2207.04672, 2022.
+
+"""
+_DESCRIPTION = """\
+
+KopI(Korpus Perayapan Indonesia)-NLLB, is Indonesian family language(aceh,bali,banjar,indonesia,jawa,minang,sunda) only extracted from NLLB Dataset, allenai/nllb
+
+each language set also filtered using some some deduplicate technique such as exact hash(md5) dedup technique and minhash LSH neardup
+
+"""
+_TYPE = ["raw", "dedup", "neardup"]
+
+
+_CONF_LANG = ["ace_Latn", "ban_Latn", "bjn_Latn", "ind_Latn", "jav_Latn", "min_Latn", "sun_Latn"]
+
+_CONFIGS = []
+for j in _CONF_LANG:
+    for m in _TYPE:
+        _CONFIGS.append(j + "-" + m)
+
+_ALL_CONFIG = ["all-raw", "all-dedup", "all-neardup"] + _CONFIGS
+
+_HOMEPAGE = "https://huggingface.co/datasets/munggok/KoPI-NLLB"
+
+_LICENSE = "ODC_C"
+
+_BASE_URL = "https://huggingface.co/datasets/munggok/KoPI-NLLB/resolve/main/{tipe}/{lang}.json.zst"
+
+_DATASETNAME = "kopi_nllb"
+
+_SUPPORTED_TASKS = [Tasks.SELF_SUPERVISED_PRETRAINING]
+
+_LANGUAGES = ["ind", "jav", "ace", "ban", "bjn", "min", "sun"]
+
+_NUSANTARA_VERSION = "1.0.0"
+
+_SOURCE_VERSION = "2022.09.13"
+
+_LOCAL = False
+
+_SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
+
+_UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
+
+_URL = "https://huggingface.co/datasets/allenai/nllb"
+
+
+def nusantara_config_constructor(lang, schema, version):
+    """Construct NusantaraConfig"""
+    if schema != "source" and schema != "nusantara_ssp":
+        raise ValueError(f"Invalid schema: {schema}")
+
+    if lang == "":
+        raise ValueError(f"Snapshot is required. Choose one of these Snapshot: {_ALL_CONFIG}.")
+    elif lang in _ALL_CONFIG:
+        return NusantaraConfig(
+            name=f"{_DATASETNAME}_{lang}_{schema}",
+            version=datasets.Version(version),
+            description=f"KoPI-NLLB with {schema} schema for {lang}",
+            schema=schema,
+            subset_id="kopi_nllb",
+        )
+    else:
+        raise ValueError(f"Invalid language: {lang}. Choose one of these snapshots: {_ALL_CONFIG}.")
+
+
+class KoPINLLBConfig(datasets.BuilderConfig):
+    """BuilderConfig for the Clean KoPI corpus."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for Clean KoPI corpus.
+        Args:
+            **kwargs: keyword arguments forwarded to super.
+        """
+        super().__init__(**kwargs)
+
+
+class KoPINLLB(datasets.GeneratorBasedBuilder):
+    """KoPI NLLB corpus."""
+
+    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"),
+                    "url": datasets.Value("string"),
+                    "score": datasets.Value("float32"),
+                    "source": 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):
+        name = self.config.name.replace("_" + self.config.schema, "")
+        name = name.replace(_DATASETNAME + "_", "")
+        split_name = name.split("-")
+        if split_name[0] == "all":
+            train = [_BASE_URL.format(tipe=split_name[1], lang=m) for m in _CONF_LANG]
+        else:
+            train = [_BASE_URL.format(tipe=split_name[1], lang=split_name[0])]
+        train_downloaded_files = dl_manager.download(train)
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files})]
+
+    def _generate_examples(self, filepaths):
+        """This function returns the examples in the raw (text) form by iterating on all the files."""
+        id_ = 0
+        for filepath in filepaths:
+            logger.info(f"Generating examples from {filepath}")
+            with zstd.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"], "source": example["source"], "score": float(example["score"])}
+                            id_ += 1