suc3.1 dataloader

suc3.1.py

@@ -0,0 +1,193 @@
+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and 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.
+
+# Lint as: python3
+"""The SuperGLUE benchmark."""
+
+import json
+import os
+
+import datasets
+
+_CITATION = """\
+@article{gustafson2006documentation,
+  title={Documentation of the Stockholm-Ume{\aa} Corpus},
+  author={Gustafson-Capkov{\'a}, Sofia and Hartmann, Britt},
+  journal={Stockholm University: Department of Linguistics},
+  year={2006}
+}
+"""
+
+# You can copy an official description
+_DESCRIPTION = """\
+    The dataset is a conversion of the venerable SUC 3.0 dataset into the
+    huggingface ecosystem. The original dataset does not contain an official
+    train-dev-test split, which is introduced here; the tag distribution for the
+    NER tags between the three splits is mostly the same.
+    
+    The dataset has three different types of tagsets: manually annotated POS,
+    manually annotated NER, and automatically annotated NER. For the
+    automatically annotated NER tags, only sentences were chosen, where the
+    automatic and manual annotations would match (with their respective
+    categories).
+    
+    Additionally we provide remixes of the same data with some or all sentences
+    being lowercased.
+"""
+
+_HOMEPAGE = "https://spraakbanken.gu.se/en/resources/suc3"
+
+_LICENSE = "CC-BY-4.0"
+
+# TODO: Add link to the official dataset URLs here
+# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_URL = "https://huggingface.co/datasets/KBLab/suc3.1/resolve/main/data/"
+_URLS = {
+    "original_tags": {
+        "cased": "original_tags/cased.tar.gz",
+        "lower": "original_tags/lower.tar.gz",
+        "lower_mix": "original_tags/lower_mixed.tar.gz"},
+    "simple_tags": {
+        "cased": "simple_tags/cased.tar.gz",
+        "lower": "simple_tags/lower.tar.gz",
+        "lower_mix": "simple_tags/lower_mixed.tar.gz"}
+}
+
+_POS_LABEL_NAMES = {
+    'AB', 'DT', 'HA', 'HD', 'HP', 'HS', 'IE', 'IN', 'JJ', 'KN', 'MAD', 'MID',
+    'NN', 'PAD', 'PC', 'PL', 'PM', 'PN', 'PP', 'PS', 'RG', 'RO', 'SN', 'UO',
+    'VB'
+}
+_NER_LABEL_NAMES_ORIGINAL = {
+    'B-animal', 'B-event', 'B-inst', 'B-myth', 'B-other', 'B-person',
+    'B-place', 'B-product', 'B-work', 'I-animal', 'I-event', 'I-inst',
+    'I-myth', 'I-other', 'I-person', 'I-place', 'I-product', 'I-work', 'O'
+}
+
+_NER_LABEL_NAMES_SIMPLE = {
+    'B-EVN', 'B-LOC', 'B-MSR', 'B-OBJ', 'B-ORG', 'B-PRS', 'B-TME', 'B-WRK',
+    'I-EVN', 'I-LOC', 'I-MSR', 'I-OBJ', 'I-ORG', 'I-PRS', 'I-TME', 'I-WRK', 'O'
+}
+
+
+class SucConfig(datasets.BuilderConfig):
+    """BuilderConfig for Suc."""
+    def __init__(self,
+                 ner_label_names,
+                 description,
+                 data_url,
+                 **kwargs):
+        """BuilderConfig for Suc.
+        """
+        # Version history:
+        # 1.0.2: Fixed non-nondeterminism in ReCoRD.
+        # 1.0.1: Change from the pre-release trial version of SuperGLUE (v1.9) to
+        #        the full release (v2.0).
+        # 1.0.0: S3 (new shuffling, sharding and slicing mechanism).
+        # 0.0.2: Initial version.
+        super(SucConfig,
+              self).__init__(version=datasets.Version("1.0.2"), **kwargs)
+        self.ner_label_names = ner_label_names
+        self.description = description
+        self.config.data_url = data_url
+
+
+
+class Suc(datasets.GeneratorBasedBuilder):
+    """The SuperGLUE benchmark."""
+
+    BUILDER_CONFIGS = [
+        SucConfig(
+            name="original_cased",
+            ner_label_names=_NER_LABEL_NAMES_ORIGINAL,
+            data_url=_URLS["original_tags"]["cased"],
+            description="manually annotated & cased",
+        ),
+        SucConfig(
+            name="original_lower",
+            ner_label_names=_NER_LABEL_NAMES_ORIGINAL,
+            data_url=_URLS["original_tags"]["lower"],
+            description="manually annotated & lower",
+        ),
+        SucConfig(
+            name="original_lower_mixed",
+            ner_label_names=_NER_LABEL_NAMES_ORIGINAL,
+            data_url=_URLS["original_tags"]["lower_mixed"],
+            description="manually annotated & lower_mixed",
+        ),
+        SucConfig(
+            name="simple_cased",
+            ner_label_names=_NER_LABEL_NAMES_SIMPLE,
+            data_url=_URLS["simple_tags"]["cased"],
+            description="automatically annotated & cased",
+        ),
+        SucConfig(
+            name="simple_lower",
+            ner_label_names=_NER_LABEL_NAMES_SIMPLE,
+            data_url=_URLS["simple_tags"]["lower"],
+            description="automatically annotated & lower",
+        ),
+        SucConfig(
+            name="simple_lower_mixed",
+            ner_label_names=_NER_LABEL_NAMES_SIMPLE,
+            data_url=_URLS["simple_tags"]["lower_mixed"],
+            description="autimatically annotated & lower_mixed",
+        ),
+    ]
+
+    def _info(self):
+        features = {"id": datasets.Value("string"),
+                    "tokens": datasets.features.Sequence(datasets.Value("string")),
+                    "pos_tags": datasets.features.Sequence(datasets.features.ClassLabel(_POS_LABEL_NAMES)),
+                    "ner_tags": datasets.features.Sequence(datasets.features.ClassLabel(self.config.ner_label_names))}
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION + self.config.description,
+            features=datasets.Features(features),
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+            supervised_keys=None,
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(_URL + self.config.data_url)
+        dl_dir = os.path.join(dl_dir)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "train.jsonl"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "dev.jsonl"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "test.jsonl"),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_file):
+        with open(data_file, encoding="utf-8") as f:
+            for line in f:
+                row = json.loads(line)
+                yield row