upload hubscripts/scielo_hub.py to hub from bigbio repo

scielo.py

@@ -0,0 +1,222 @@
+# 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.
+"""
+Parallel corpus of full-text articles in Portuguese, English and Spanish from SciELO.
+"""
+from typing import IO, Any, Generator, List, Optional, Tuple
+
+import datasets
+
+from .bigbiohub import text2text_features
+from .bigbiohub import BigBioConfig
+from .bigbiohub import Tasks
+
+_LANGUAGES = ['English', 'Spanish', 'Portuguese']
+_PUBMED = False
+_LOCAL = False
+_CITATION = """\
+@inproceedings{soares2018large,
+  title        = {A Large Parallel Corpus of Full-Text Scientific Articles},
+  author       = {Soares, Felipe and Moreira, Viviane and Becker, Karin},
+  year         = 2018,
+  booktitle    = {
+    Proceedings of the Eleventh International Conference on Language Resources
+    and Evaluation (LREC-2018)
+  }
+}
+"""
+
+_DATASETNAME = "scielo"
+_DISPLAYNAME = "SciELO"
+
+_DESCRIPTION = """\
+A parallel corpus of full-text scientific articles collected from Scielo \
+database in the following languages: English, Portuguese and Spanish. The corpus \
+is sentence aligned for all language pairs, as well as trilingual aligned for a \
+small subset of sentences. Alignment was carried out using the Hunalign \
+algorithm.
+"""
+
+_HOMEPAGE = "https://sites.google.com/view/felipe-soares/datasets#h.p_92uSCyAjWSRB"
+
+_LICENSE = 'Creative Commons Attribution 4.0 International'
+
+_URLS = {
+    "en_es": "https://ndownloader.figstatic.com/files/14019287",
+    "en_pt": "https://ndownloader.figstatic.com/files/14019308",
+    "en_pt_es": "https://ndownloader.figstatic.com/files/14019293",
+}
+
+_SUPPORTED_TASKS = [Tasks.TRANSLATION]
+
+_SOURCE_VERSION = "1.0.0"
+_BIGBIO_VERSION = "1.0.0"
+
+
+class ScieloDataset(datasets.GeneratorBasedBuilder):
+    """Parallel corpus of full-text articles in Portuguese, English and Spanish from SciELO."""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    BIGBIO_VERSION = datasets.Version(_BIGBIO_VERSION)
+
+    # NOTE: bigbio_t2t schema doesn't allow only for more than two texts in text-to-text schema.
+    #  en-pt-es translation is not implemented using the bigbio schema
+
+    BUILDER_CONFIGS = [
+        BigBioConfig(
+            name="scielo_en_es_source",
+            version=SOURCE_VERSION,
+            description="English-Spanish",
+            schema="source",
+            subset_id="scielo_en_es",
+        ),
+        BigBioConfig(
+            name="scielo_en_pt_source",
+            version=SOURCE_VERSION,
+            description="English-Portuguese",
+            schema="source",
+            subset_id="scielo_en_pt",
+        ),
+        BigBioConfig(
+            name="scielo_en_pt_es_source",
+            version=SOURCE_VERSION,
+            description="English-Portuguese-Spanish",
+            schema="source",
+            subset_id="scielo_en_pt_es",
+        ),
+        BigBioConfig(
+            name="scielo_en_es_bigbio_t2t",
+            version=BIGBIO_VERSION,
+            description="scielo BigBio schema English-Spanish",
+            schema="bigbio_t2t",
+            subset_id="scielo_en_es",
+        ),
+        BigBioConfig(
+            name="scielo_en_pt_bigbio_t2t",
+            version=BIGBIO_VERSION,
+            description="scielo BigBio schema English-Portuguese",
+            schema="bigbio_t2t",
+            subset_id="scielo_en_pt",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "scielo_source_en_es"
+
+    def _info(self) -> datasets.DatasetInfo:
+
+        if self.config.schema == "source":
+            lang_list: List[str] = self.config.subset_id.split("_")[1:]
+            features = datasets.Features(
+                {"translation": datasets.features.Translation(languages=lang_list)}
+            )
+
+        elif self.config.schema == "bigbio_t2t":
+            features = text2text_features
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=str(_LICENSE),
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager) -> List[datasets.SplitGenerator]:
+        """Returns SplitGenerators."""
+        lang_list: List[str] = self.config.subset_id.split("_")[1:]
+        languages = "_".join(lang_list)
+        archive = dl_manager.download(_URLS[languages])
+
+        fname = languages
+
+        if languages == "en_pt_es":
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "source_file": f"{fname}.en",
+                        "target_file": f"{fname}.pt",
+                        "target_file_2": f"{fname}.es",
+                        "files": dl_manager.iter_archive(archive),
+                        "languages": languages,
+                        "split": "train",
+                    },
+                ),
+            ]
+        else:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "source_file": f"{fname}.{lang_list[0]}",
+                        "target_file": f"{fname}.{lang_list[1]}",
+                        "files": dl_manager.iter_archive(archive),
+                        "languages": languages,
+                        "split": "train",
+                    },
+                ),
+            ]
+
+    def _generate_examples(
+        self,
+        languages: str,
+        split: str,
+        source_file: str,
+        target_file: str,
+        files: Generator[Tuple[str, IO[bytes]], Any, None],
+        target_file_2: Optional[str] = None,
+    ) -> Tuple[int, dict]:
+
+        if self.config.schema == "source":
+            for path, f in files:
+                if path == source_file:
+                    source_sentences = f.read().decode("utf-8").split("\n")
+                elif path == target_file:
+                    target_sentences = f.read().decode("utf-8").split("\n")
+                elif languages == "en_pt_es" and path == target_file_2:
+                    target_sentences_2 = f.read().decode("utf-8").split("\n")
+
+            if languages == "en_pt_es":
+                source, target, target_2 = tuple(languages.split("_"))
+                for idx, (l1, l2, l3) in enumerate(
+                    zip(source_sentences, target_sentences, target_sentences_2)
+                ):
+                    result = {"translation": {source: l1, target: l2, target_2: l3}}
+                    yield idx, result
+            else:
+                source, target = tuple(languages.split("_"))
+                for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)):
+                    result = {"translation": {source: l1, target: l2}}
+                    yield idx, result
+
+        elif self.config.schema == "bigbio_t2t":
+            for path, f in files:
+                if path == source_file:
+                    source_sentences = f.read().decode("utf-8").split("\n")
+                elif path == target_file:
+                    target_sentences = f.read().decode("utf-8").split("\n")
+
+            uid = 0
+            source, target = tuple(languages.split("_"))
+            for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)):
+                uid += 1
+                yield idx, {
+                    "id": str(uid),
+                    "document_id": str(idx),
+                    "text_1": l1,
+                    "text_2": l2,
+                    "text_1_name": source,
+                    "text_2_name": target,
+                }