Datasets:

Modalities:
Text
Formats:
parquet
Sub-tasks:
extractive-qa
Languages:
English
ArXiv:
Libraries:
Datasets
pandas
License:
albertvillanova HF staff commited on
Commit
0a3a8b7
1 Parent(s): 5fe18c4

Convert dataset to Parquet (#7)

Browse files

- Convert dataset to Parquet (06709de10ef08fc185216197b2819f24e8a40b3a)
- Delete loading script (9dab3f0a2e206e11b872424260872686647d63e1)
- Delete legacy dataset_infos.json (2d731f5185a5a9a7e515100d449803ab41930dcc)

README.md CHANGED
@@ -1,5 +1,4 @@
1
  ---
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- pretty_name: SQuAD
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  annotations_creators:
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  - crowdsourced
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  language_creators:
@@ -20,23 +19,9 @@ task_categories:
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  task_ids:
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  - extractive-qa
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  paperswithcode_id: squad
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- train-eval-index:
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- - config: plain_text
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- task: question-answering
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- task_id: extractive_question_answering
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- splits:
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- train_split: train
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- eval_split: validation
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- col_mapping:
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- question: question
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- context: context
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- answers:
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- text: text
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- answer_start: answer_start
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- metrics:
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- - type: squad
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- name: SQuAD
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  dataset_info:
 
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  features:
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  - name: id
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  dtype: string
@@ -52,16 +37,39 @@ dataset_info:
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  dtype: string
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  - name: answer_start
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  dtype: int32
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- config_name: plain_text
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  splits:
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  - name: train
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- num_bytes: 79317110
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  num_examples: 87599
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  - name: validation
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- num_bytes: 10472653
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  num_examples: 10570
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- download_size: 35142551
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- dataset_size: 89789763
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Dataset Card for "squad"
 
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  ---
 
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  annotations_creators:
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  - crowdsourced
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  language_creators:
 
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  task_ids:
20
  - extractive-qa
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  paperswithcode_id: squad
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+ pretty_name: SQuAD
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  dataset_info:
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+ config_name: plain_text
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  features:
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  - name: id
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  dtype: string
 
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  dtype: string
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  - name: answer_start
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  dtype: int32
 
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  splits:
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  - name: train
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+ num_bytes: 79346108
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  num_examples: 87599
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  - name: validation
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+ num_bytes: 10472984
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  num_examples: 10570
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+ download_size: 16278203
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+ dataset_size: 89819092
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+ configs:
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+ - config_name: plain_text
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+ data_files:
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+ - split: train
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+ path: plain_text/train-*
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+ - split: validation
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+ path: plain_text/validation-*
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+ default: true
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+ train-eval-index:
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+ - config: plain_text
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+ task: question-answering
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+ task_id: extractive_question_answering
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+ splits:
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+ train_split: train
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+ eval_split: validation
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+ col_mapping:
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+ question: question
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+ context: context
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+ answers:
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+ text: text
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+ answer_start: answer_start
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+ metrics:
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+ - type: squad
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+ name: SQuAD
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  ---
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  # Dataset Card for "squad"
dataset_infos.json DELETED
@@ -1 +0,0 @@
1
- {"plain_text": {"description": "Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.\n", "citation": "@article{2016arXiv160605250R,\n author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},\n Konstantin and {Liang}, Percy},\n title = \"{SQuAD: 100,000+ Questions for Machine Comprehension of Text}\",\n journal = {arXiv e-prints},\n year = 2016,\n eid = {arXiv:1606.05250},\n pages = {arXiv:1606.05250},\narchivePrefix = {arXiv},\n eprint = {1606.05250},\n}\n", "homepage": "https://rajpurkar.github.io/SQuAD-explorer/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "question-answering-extractive", "question_column": "question", "context_column": "context", "answers_column": "answers"}], "builder_name": "squad", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 79317110, "num_examples": 87599, "dataset_name": "squad"}, "validation": {"name": "validation", "num_bytes": 10472653, "num_examples": 10570, "dataset_name": "squad"}}, "download_checksums": {"https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json": {"num_bytes": 30288272, "checksum": "3527663986b8295af4f7fcdff1ba1ff3f72d07d61a20f487cb238a6ef92fd955"}, "https://rajpurkar.github.io/SQuAD-explorer/dataset/dev-v1.1.json": {"num_bytes": 4854279, "checksum": "95aa6a52d5d6a735563366753ca50492a658031da74f301ac5238b03966972c9"}}, "download_size": 35142551, "post_processing_size": null, "dataset_size": 89789763, "size_in_bytes": 124932314}}
 
 
plain_text/train-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:ea7f52bac024f6b1bdc7aaa2a4ee302cba8c2fdc8d4a235cf18a9a5196b6175b
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+ size 14458314
plain_text/validation-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:8c6646d36bd5a95061e076788cf3161d11f6f3e7d625dac7a83bbed0a49f69f7
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+ size 1819889
squad.py DELETED
@@ -1,142 +0,0 @@
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- # coding=utf-8
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- # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
12
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
14
- # limitations under the License.
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-
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- # Lint as: python3
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- """SQUAD: The Stanford Question Answering Dataset."""
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-
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-
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- import json
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-
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- import datasets
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- from datasets.tasks import QuestionAnsweringExtractive
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-
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-
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- logger = datasets.logging.get_logger(__name__)
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-
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-
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- _CITATION = """\
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- @article{2016arXiv160605250R,
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- author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
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- Konstantin and {Liang}, Percy},
33
- title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
34
- journal = {arXiv e-prints},
35
- year = 2016,
36
- eid = {arXiv:1606.05250},
37
- pages = {arXiv:1606.05250},
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- archivePrefix = {arXiv},
39
- eprint = {1606.05250},
40
- }
41
- """
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-
43
- _DESCRIPTION = """\
44
- Stanford Question Answering Dataset (SQuAD) is a reading comprehension \
45
- dataset, consisting of questions posed by crowdworkers on a set of Wikipedia \
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- articles, where the answer to every question is a segment of text, or span, \
47
- from the corresponding reading passage, or the question might be unanswerable.
48
- """
49
-
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- _URL = "https://rajpurkar.github.io/SQuAD-explorer/dataset/"
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- _URLS = {
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- "train": _URL + "train-v1.1.json",
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- "dev": _URL + "dev-v1.1.json",
54
- }
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-
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-
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- class SquadConfig(datasets.BuilderConfig):
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- """BuilderConfig for SQUAD."""
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-
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- def __init__(self, **kwargs):
61
- """BuilderConfig for SQUAD.
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-
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- Args:
64
- **kwargs: keyword arguments forwarded to super.
65
- """
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- super(SquadConfig, self).__init__(**kwargs)
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-
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-
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- class Squad(datasets.GeneratorBasedBuilder):
70
- """SQUAD: The Stanford Question Answering Dataset. Version 1.1."""
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-
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- BUILDER_CONFIGS = [
73
- SquadConfig(
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- name="plain_text",
75
- version=datasets.Version("1.0.0", ""),
76
- description="Plain text",
77
- ),
78
- ]
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-
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- def _info(self):
81
- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=datasets.Features(
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- {
85
- "id": datasets.Value("string"),
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- "title": datasets.Value("string"),
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- "context": datasets.Value("string"),
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- "question": datasets.Value("string"),
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- "answers": datasets.features.Sequence(
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- {
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- "text": datasets.Value("string"),
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- "answer_start": datasets.Value("int32"),
93
- }
94
- ),
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- }
96
- ),
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- # No default supervised_keys (as we have to pass both question
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- # and context as input).
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- supervised_keys=None,
100
- homepage="https://rajpurkar.github.io/SQuAD-explorer/",
101
- citation=_CITATION,
102
- task_templates=[
103
- QuestionAnsweringExtractive(
104
- question_column="question", context_column="context", answers_column="answers"
105
- )
106
- ],
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- )
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-
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- def _split_generators(self, dl_manager):
110
- downloaded_files = dl_manager.download_and_extract(_URLS)
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-
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- return [
113
- datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
114
- datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
115
- ]
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-
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- def _generate_examples(self, filepath):
118
- """This function returns the examples in the raw (text) form."""
119
- logger.info("generating examples from = %s", filepath)
120
- key = 0
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- with open(filepath, encoding="utf-8") as f:
122
- squad = json.load(f)
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- for article in squad["data"]:
124
- title = article.get("title", "")
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- for paragraph in article["paragraphs"]:
126
- context = paragraph["context"] # do not strip leading blank spaces GH-2585
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- for qa in paragraph["qas"]:
128
- answer_starts = [answer["answer_start"] for answer in qa["answers"]]
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- answers = [answer["text"] for answer in qa["answers"]]
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- # Features currently used are "context", "question", and "answers".
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- # Others are extracted here for the ease of future expansions.
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- yield key, {
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- "title": title,
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- "context": context,
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- "question": qa["question"],
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- "id": qa["id"],
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- "answers": {
138
- "answer_start": answer_starts,
139
- "text": answers,
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- },
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- }
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- key += 1