Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- found
+languages:
+- pt
+licenses:
+- cc-by-4-0
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+task_ids:
+- structure-prediction-other-part-of-speech-tagging
+---
+
+# Dataset Card for Mac-Morpho
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** [Mac-Morpho homepage](http://nilc.icmc.usp.br/macmorpho/)
+- **Repository:** [Mac-Morpho repository](http://nilc.icmc.usp.br/macmorpho/)
+- **Paper:** [Evaluating word embeddings and a revised corpus for part-of-speech tagging in Portuguese](https://journal-bcs.springeropen.com/articles/10.1186/s13173-014-0020-x)
+- **Point of Contact:** [Erick R Fonseca](mailto:[email protected])
+
+### Dataset Summary
+
+Mac-Morpho is a corpus of Brazilian Portuguese texts annotated with part-of-speech tags. 
+Its first version was released in 2003 [1], and since then, two revisions have been made in order 
+to improve the quality of the resource [2, 3].
+The corpus is available for download split into train, development and test sections. 
+These are 76%, 4% and 20% of the corpus total, respectively (the reason for the unusual numbers 
+is that the corpus was first split into 80%/20% train/test, and then 5% of the train section was 
+set aside for development). This split was used in [3], and new POS tagging research with Mac-Morpho 
+is encouraged to follow it in order to make consistent comparisons possible.
+
+
+[1] Aluísio, S., Pelizzoni, J., Marchi, A.R., de Oliveira, L., Manenti, R., Marquiafável, V. 2003. 
+An account of the challenge of tagging a reference corpus for brazilian portuguese. 
+In: Proceedings of the 6th International Conference on Computational Processing of the Portuguese Language. PROPOR 2003
+
+[2] Fonseca, E.R., Rosa, J.L.G. 2013. Mac-morpho revisited: Towards robust part-of-speech. 
+In: Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology – STIL
+
+[3] Fonseca, E.R., Aluísio, Sandra Maria, Rosa, J.L.G. 2015. 
+Evaluating word embeddings and a revised corpus for part-of-speech tagging in Portuguese. 
+Journal of the Brazilian Computer Society.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+Portuguese
+
+## Dataset Structure
+
+### Data Instances
+
+An example from the Mac-Morpho dataset looks as follows:
+
+```
+{
+    "id": "0",
+    "pos_tags": [14, 19, 14, 15, 22, 7, 14, 9, 14, 9, 3, 15, 3, 3, 24],
+    "tokens": ["Jersei", "atinge", "média", "de", "Cr$", "1,4", "milhão", "na", "venda", "da", "Pinhal", "em", "São", "Paulo", "."]
+}
+```
+
+### Data Fields
+
+- `id`: id of the sample
+- `tokens`: the tokens of the example text
+- `pos`: the PoS tags of each token
+
+The PoS tags correspond to this list:
+```
+"PREP+PROADJ", "IN", "PREP+PRO-KS", "NPROP", "PREP+PROSUB", "KC", "PROPESS", "NUM", "PROADJ", "PREP+ART", "KS", 
+"PRO-KS", "ADJ", "ADV-KS", "N", "PREP", "PROSUB", "PREP+PROPESS", "PDEN", "V", "PREP+ADV", "PCP", "CUR", "ADV", "PU", "ART"
+```
+
+### Data Splits
+
+The data is split into train, validation and test set. The split sizes are as follow:
+
+| Train  | Val   | Test  |
+| ------ | ----- | ----- |
+| 37948  | 1997  | 9987  |
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+```
+@article{fonseca2015evaluating,
+  title={Evaluating word embeddings and a revised corpus for part-of-speech tagging in Portuguese},
+  author={Fonseca, Erick R and Rosa, Jo{\~a}o Lu{\'\i}s G and Alu{\'\i}sio, Sandra Maria},
+  journal={Journal of the Brazilian Computer Society},
+  volume={21},
+  number={1},
+  pages={2},
+  year={2015},
+  publisher={Springer}
+}
+```

dataset_infos.json

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+{"default": {"description": "\nMac-Morpho is a corpus of Brazilian Portuguese texts annotated with part-of-speech tags.\nIts first version was released in 2003 [1], and since then, two revisions have been made in order\nto improve the quality of the resource [2, 3].\nThe corpus is available for download split into train, development and test sections.\nThese are 76%, 4% and 20% of the corpus total, respectively (the reason for the unusual numbers\nis that the corpus was first split into 80%/20% train/test, and then 5% of the train section was\nset aside for development). This split was used in [3], and new POS tagging research with Mac-Morpho\nis encouraged to follow it in order to make consistent comparisons possible.\n\n\n[1] Alu\u00edsio, S., Pelizzoni, J., Marchi, A.R., de Oliveira, L., Manenti, R., Marquiaf\u00e1vel, V. 2003.\nAn account of the challenge of tagging a reference corpus for brazilian portuguese.\nIn: Proceedings of the 6th International Conference on Computational Processing of the Portuguese Language. PROPOR 2003\n\n[2] Fonseca, E.R., Rosa, J.L.G. 2013. Mac-morpho revisited: Towards robust part-of-speech.\nIn: Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology \u2013 STIL\n\n[3] Fonseca, E.R., Alu\u00edsio, Sandra Maria, Rosa, J.L.G. 2015.\nEvaluating word embeddings and a revised corpus for part-of-speech tagging in Portuguese.\nJournal of the Brazilian Computer Society.\n", "citation": "\n@article{fonseca2015evaluating,\n  title={Evaluating word embeddings and a revised corpus for part-of-speech tagging in Portuguese},\n  author={Fonseca, Erick R and Rosa, Joao Luis G and Aluisio, Sandra Maria},\n  journal={Journal of the Brazilian Computer Society},\n  volume={21},\n  number={1},\n  pages={2},\n  year={2015},\n  publisher={Springer}\n}\n", "homepage": "http://www.nilc.icmc.usp.br/macmorpho/", "license": "Creative Commons Attribution 4.0 International License", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "pos_tags": {"feature": {"num_classes": 26, "names": ["PREP+PROADJ", "IN", "PREP+PRO-KS", "NPROP", "PREP+PROSUB", "KC", "PROPESS", "NUM", "PROADJ", "PREP+ART", "KS", "PRO-KS", "ADJ", "ADV-KS", "N", "PREP", "PROSUB", "PREP+PROPESS", "PDEN", "V", "PREP+ADV", "PCP", "CUR", "ADV", "PU", "ART"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "mac_morpho", "config_name": "default", "version": {"version_str": "3.0.0", "description": null, "major": 3, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 12635011, "num_examples": 37948, "dataset_name": "mac_morpho"}, "test": {"name": "test", "num_bytes": 3095292, "num_examples": 9987, "dataset_name": "mac_morpho"}, "validation": {"name": "validation", "num_bytes": 671356, "num_examples": 1997, "dataset_name": "mac_morpho"}}, "download_checksums": {"http://www.nilc.icmc.usp.br/macmorpho/macmorpho-v3.tgz": {"num_bytes": 2463485, "checksum": "454bd299166ab511547be43bba8b52473f8de2c69894fbb8a62a657a8d7ac52b"}}, "download_size": 2463485, "post_processing_size": null, "dataset_size": 16401659, "size_in_bytes": 18865144}}

dummy/3.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ccf8af274c0e9e47016bb7f00d9d1e041ad1f78e3a92b6f7057e68e1c133482f
+size 2130

mac_morpho.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.
+"""Mac-Morpho dataset"""
+
+from __future__ import absolute_import, division, print_function
+
+import logging
+import os
+import re
+
+import datasets
+
+
+_CITATION = """
+@article{fonseca2015evaluating,
+  title={Evaluating word embeddings and a revised corpus for part-of-speech tagging in Portuguese},
+  author={Fonseca, Erick R and Rosa, Joao Luis G and Aluisio, Sandra Maria},
+  journal={Journal of the Brazilian Computer Society},
+  volume={21},
+  number={1},
+  pages={2},
+  year={2015},
+  publisher={Springer}
+}
+"""
+
+_DESCRIPTION = """
+Mac-Morpho is a corpus of Brazilian Portuguese texts annotated with part-of-speech tags.
+Its first version was released in 2003 [1], and since then, two revisions have been made in order
+to improve the quality of the resource [2, 3].
+The corpus is available for download split into train, development and test sections.
+These are 76%, 4% and 20% of the corpus total, respectively (the reason for the unusual numbers
+is that the corpus was first split into 80%/20% train/test, and then 5% of the train section was
+set aside for development). This split was used in [3], and new POS tagging research with Mac-Morpho
+is encouraged to follow it in order to make consistent comparisons possible.
+
+
+[1] Aluísio, S., Pelizzoni, J., Marchi, A.R., de Oliveira, L., Manenti, R., Marquiafável, V. 2003.
+An account of the challenge of tagging a reference corpus for brazilian portuguese.
+In: Proceedings of the 6th International Conference on Computational Processing of the Portuguese Language. PROPOR 2003
+
+[2] Fonseca, E.R., Rosa, J.L.G. 2013. Mac-morpho revisited: Towards robust part-of-speech.
+In: Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology – STIL
+
+[3] Fonseca, E.R., Aluísio, Sandra Maria, Rosa, J.L.G. 2015.
+Evaluating word embeddings and a revised corpus for part-of-speech tagging in Portuguese.
+Journal of the Brazilian Computer Society.
+"""
+
+_HOMEPAGE = "http://www.nilc.icmc.usp.br/macmorpho/"
+
+_LICENSE = "Creative Commons Attribution 4.0 International License"
+
+_URL = "http://www.nilc.icmc.usp.br/macmorpho/macmorpho-v3.tgz"
+
+
+class MacMorpho(datasets.GeneratorBasedBuilder):
+    """Mac-Morpho dataset."""
+
+    VERSION = datasets.Version("3.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "pos_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "PREP+PROADJ",
+                                "IN",
+                                "PREP+PRO-KS",
+                                "NPROP",
+                                "PREP+PROSUB",
+                                "KC",
+                                "PROPESS",
+                                "NUM",
+                                "PROADJ",
+                                "PREP+ART",
+                                "KS",
+                                "PRO-KS",
+                                "ADJ",
+                                "ADV-KS",
+                                "N",
+                                "PREP",
+                                "PROSUB",
+                                "PREP+PROPESS",
+                                "PDEN",
+                                "V",
+                                "PREP+ADV",
+                                "PCP",
+                                "CUR",
+                                "ADV",
+                                "PU",
+                                "ART",
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_dir = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "macmorpho-train.txt"),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": os.path.join(data_dir, "macmorpho-test.txt"), "split": "test"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "macmorpho-dev.txt"),
+                    "split": "dev",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        """ Yields examples. """
+        logging.info("⏳ Generating examples from = %s", filepath)
+
+        with open(filepath, "r", encoding="utf-8") as f:
+
+            id_ = 0
+
+            for line in f:
+
+                line = line.rstrip()
+                chunks = re.split(r"\s+", line)
+
+                tokens = []
+                pos_tags = []
+                for chunk in chunks:
+                    token, tag = chunk.rsplit("_", 1)
+                    tokens.append(token)
+                    pos_tags.append(tag)
+
+                yield id_, {
+                    "id": str(id_),
+                    "tokens": tokens,
+                    "pos_tags": pos_tags,
+                }
+                id_ += 1