Convert dataset to Parquet (#3)

- Convert dataset to Parquet (01fdde27e129e5ea4e89f98a4ba62917e5ad11b2)
- Delete loading script (b023a2bc2f6e9345b2f741026a16b30b5786eee8)

README.md

@@ -17,9 +17,9 @@ task_categories:
 - question-answering
 task_ids:
 - extractive-qa
-paperswithcode_id: null
 pretty_name: PersiNLU (Reading Comprehension)
 dataset_info:
+  config_name: parsinlu-repo
   features:
   - name: question
     dtype: string
@@ -33,10 +33,9 @@ dataset_info:
       dtype: int32
     - name: answer_text
       dtype: string
-  config_name: parsinlu-repo
   splits:
   - name: train
-    num_bytes: 747679
+    num_bytes: 747655
     num_examples: 600
   - name: test
     num_bytes: 674711
@@ -44,8 +43,18 @@ dataset_info:
   - name: validation
     num_bytes: 163161
     num_examples: 125
-  download_size: 4105495
+  download_size: 777432
   dataset_size: 1585527
+configs:
+- config_name: parsinlu-repo
+  data_files:
+  - split: train
+    path: parsinlu-repo/train-*
+  - split: test
+    path: parsinlu-repo/test-*
+  - split: validation
+    path: parsinlu-repo/validation-*
+  default: true
 ---
 
 # Dataset Card for PersiNLU (Reading Comprehension)

parsinlu-repo/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f35779d9faf2121f5953df218d49fa3f69cd3d52f3d024a60d2818d4378bf144
+size 322212

parsinlu-repo/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bbe7e80fcc73c488a0c5839ee9b4b16d12bc40d3295a98f71897113b6aeb7415
+size 363239

parsinlu-repo/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cb86eed5f155eef8bf7428d2680da48be30e0ac737c353e7f30729fed260ec5
+size 91981

parsinlu_reading_comprehension.py

@@ -1,141 +0,0 @@
-# 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.
-"""ParsiNLU Persian reading comprehension task"""
-
-
-import json
-
-import datasets
-
-
-logger = datasets.logging.get_logger(__name__)
-
-_CITATION = """\
-@article{huggingface:dataset,
-    title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
-    authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian, Sarik and others},
-    year={2020}
-    journal = {arXiv e-prints},
-    eprint = {2012.06154},
-}
-"""
-
-# You can copy an official description
-_DESCRIPTION = """\
-A Persian reading comprehenion task (generating an answer, given a question and a context paragraph).
-The questions are mined using Google auto-complete, their answers and the corresponding evidence documents are manually annotated by native speakers.
-"""
-
-_HOMEPAGE = "https://github.com/persiannlp/parsinlu/"
-
-_LICENSE = "CC BY-NC-SA 4.0"
-
-_URL = "https://raw.githubusercontent.com/persiannlp/parsinlu/master/data/reading_comprehension/"
-_URLs = {
-    "train": _URL + "train.jsonl",
-    "dev": _URL + "dev.jsonl",
-    "test": _URL + "eval.jsonl",
-}
-
-
-class ParsinluReadingComprehension(datasets.GeneratorBasedBuilder):
-    """ParsiNLU Persian reading comprehension task."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="parsinlu-repo", version=VERSION, description="ParsiNLU repository: reading-comprehension"
-        ),
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "question": datasets.Value("string"),
-                "url": datasets.Value("string"),
-                "context": datasets.Value("string"),
-                "answers": datasets.features.Sequence(
-                    {
-                        "answer_start": datasets.Value("int32"),
-                        "answer_text": datasets.Value("string"),
-                    }
-                ),
-            }
-        )
-
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage=_HOMEPAGE,
-            # License for the dataset if available
-            license=_LICENSE,
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download_and_extract(_URLs)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": data_dir["train"],
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": data_dir["test"], "split": "test"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": data_dir["dev"],
-                    "split": "dev",
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        logger.info("generating examples from = %s", filepath)
-
-        def get_answer_index(passage, answer):
-            return passage.index(answer) if answer in passage else -1
-
-        with open(filepath, encoding="utf-8") as f:
-            for id_, row in enumerate(f):
-                data = json.loads(row)
-                answer = data["answers"]
-                if type(answer[0]) == str:
-                    answer = [{"answer_start": get_answer_index(data["passage"], x), "answer_text": x} for x in answer]
-                else:
-                    answer = [{"answer_start": x[0], "answer_text": x[1]} for x in answer]
-                yield id_, {
-                    "question": data["question"],
-                    "url": str(data["url"]),
-                    "context": data["passage"],
-                    "answers": answer,
-                }