Convert dataset to Parquet (#2)

- Convert dataset to Parquet (cd230d3eb6990eb7f41f51fb5b3f98a8339c4f41)
- Add 'en-pt' config data files (ee2c9e52a3e2d7e39a4e3a111578517bf9150f8b)
- Add 'en-pt-es' config data files (8ed6ec74c8946f7c9e6792bb3c5b0b9d8a386b8c)
- Delete loading script (b1f0cde511275292095af5238c81f80f464ef200)

README.md

@@ -18,8 +18,11 @@ source_datasets:
 task_categories:
 - translation
 task_ids: []
-paperswithcode_id: null
 pretty_name: SciELO
+config_names:
+- en-es
+- en-pt
+- en-pt-es
 dataset_info:
 - config_name: en-es
   features:
@@ -31,10 +34,10 @@ dataset_info:
         - es
   splits:
   - name: train
-    num_bytes: 71777213
+    num_bytes: 71777069
     num_examples: 177782
-  download_size: 22965217
-  dataset_size: 71777213
+  download_size: 39938803
+  dataset_size: 71777069
 - config_name: en-pt
   features:
   - name: translation
@@ -45,10 +48,10 @@ dataset_info:
         - pt
   splits:
   - name: train
-    num_bytes: 1032669686
+    num_bytes: 1032667422
     num_examples: 2828917
-  download_size: 322726075
-  dataset_size: 1032669686
+  download_size: 565678928
+  dataset_size: 1032667422
 - config_name: en-pt-es
   features:
   - name: translation
@@ -60,14 +63,23 @@ dataset_info:
         - es
   splits:
   - name: train
-    num_bytes: 147472132
+    num_bytes: 147471820
     num_examples: 255915
-  download_size: 45556562
-  dataset_size: 147472132
-config_names:
-- en-es
-- en-pt
-- en-pt-es
+  download_size: 80329522
+  dataset_size: 147471820
+configs:
+- config_name: en-es
+  data_files:
+  - split: train
+    path: en-es/train-*
+- config_name: en-pt
+  data_files:
+  - split: train
+    path: en-pt/train-*
+- config_name: en-pt-es
+  data_files:
+  - split: train
+    path: en-pt-es/train-*
 ---
 
 # Dataset Card for SciELO

en-es/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:143ad22a514c530dc56e50346ecacc18447ac1dfffdd2ea085c4d85475fe677a
+size 39938803

en-pt-es/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:38e186aad1c4c0c629330055a7540596085ff811bd637bc00bb605da35b9d898
+size 80329522

en-pt/train-00000-of-00003.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7275ed1077c3307c878aee1847d44379b9b826a7510a00ae77e7c8ff1f088924
+size 188756689

en-pt/train-00001-of-00003.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3e286a4d195ca56bf7d811200fe661af17701e0cb385f76c01ecd17702a26bb2
+size 188307047

en-pt/train-00002-of-00003.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6ec47130a6243d67ee39ec76bd0030a979bf285c438ac19042bdce668b0f4dfa
+size 188615192

scielo.py

@@ -1,121 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors.
-#
-# 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"""
-
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{soares2018large,
-  title={A Large Parallel Corpus of Full-Text Scientific Articles},
-  author={Soares, Felipe and Moreira, Viviane and Becker, Karin},
-  booktitle={Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC-2018)},
-  year={2018}
-}
-"""
-
-
-_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"
-
-_LANGUAGES = ["en-es", "en-pt", "en-pt-es"]
-
-_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",
-}
-
-
-class Scielo(datasets.GeneratorBasedBuilder):
-    """Parallel corpus of full-text articles in Portuguese, English and Spanish from SciELO"""
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="en-es", version=datasets.Version("1.0.0"), description="English-Spanish"),
-        datasets.BuilderConfig(name="en-pt", version=datasets.Version("1.0.0"), description="English-Portuguese"),
-        datasets.BuilderConfig(
-            name="en-pt-es", version=datasets.Version("1.0.0"), description="English-Portuguese-Spanish"
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {"translation": datasets.features.Translation(languages=tuple(self.config.name.split("-")))}
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        archive = dl_manager.download(_URLS[self.config.name])
-        lang_pair = self.config.name.split("-")
-        fname = self.config.name.replace("-", "_")
-
-        if self.config.name == "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),
-                    },
-                ),
-            ]
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "source_file": f"{fname}.{lang_pair[0]}",
-                    "target_file": f"{fname}.{lang_pair[1]}",
-                    "files": dl_manager.iter_archive(archive),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, source_file, target_file, files, target_file_2=None):
-        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 self.config.name == "en-pt-es" and path == target_file_2:
-                target_sentences_2 = f.read().decode("utf-8").split("\n")
-
-        if self.config.name == "en-pt-es":
-            source, target, target_2 = tuple(self.config.name.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(self.config.name.split("-"))
-            for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)):
-                result = {"translation": {source: l1, target: l2}}
-                yield idx, result