minor

TopiOCQA.py

@@ -1,128 +0,0 @@
-# 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
-"""TopiOCQA: Open-domain Conversational Question Answering with Topic Switching"""
-
-
-import json
-
-import datasets
-# from datasets.tasks import QuestionAnsweringExtractive
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-# _CITATION = """\
-# @article{2016arXiv160605250R,
-#        author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
-#                  Konstantin and {Liang}, Percy},
-#         title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
-#       journal = {arXiv e-prints},
-#          year = 2016,
-#           eid = {arXiv:1606.05250},
-#         pages = {arXiv:1606.05250},
-# archivePrefix = {arXiv},
-#        eprint = {1606.05250},
-# }
-# """
-
-_DESCRIPTION = """\
-TopiOCQA is an information-seeking conversational dataset with challenging topic switching phenomena.
-"""
-
-# _URL = "https://rajpurkar.github.io/SQuAD-explorer/dataset/"
-_URLS = {
-    "train": "data/topiocqa_train.jsonl",
-    "valid": "data/topiocqa_valid.jsonl",
-}
-
-
-class TopiOCQAConfig(datasets.BuilderConfig):
-    """BuilderConfig for SQUAD."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for TopiOCQA.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(TopiOCQAConfig, self).__init__(**kwargs)
-
-
-class Squad(datasets.GeneratorBasedBuilder):
-    """SQUAD: The Stanford Question Answering Dataset. Version 1.1."""
-
-    BUILDER_CONFIGS = [
-        TopiOCQAConfig(
-            name="plain_text",
-            version=datasets.Version("1.0.0", ""),
-            description="Plain text",
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "Conversation_no": datasets.Value("int32"),
-                    "Turn_no": datasets.Value("int32"),
-                    "Question": datasets.Value("string"),
-                    "Answer": datasets.Value("string"),
-                    "Topic": datasets.Value("string"),
-                    "Topic_section": datasets.Value("string"),
-                    "Rationale": datasets.Value("string"),
-                    "is_nq": datasets.Value("bool"),
-                    "Context": datasets.features.Sequence(datasets.Value("string")),
-                    "Additional_answers": datasets.features.Sequence(
-                        {
-                            "Answer": datasets.Value("string"),
-                            "Topic": datasets.Value("string"),
-                            "Topic_section": datasets.Value("string"),
-                            "Rationale": datasets.Value("string"),
-                        }
-                    ),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://mcgill-nlp.github.io/topiocqa/",
-            # citation=_CITATION,
-            # task_templates=[
-            #     QuestionAnsweringExtractive(
-            #         question_column="Question", context_column="context", answers_column="answers"
-            #     )
-            # ],
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download_and_extract(_URLS)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["valid"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        """This function returns the examples in the raw (text) form."""
-        logger.info("generating examples from = %s", filepath)
-        key = 0
-        with open(filepath, encoding="utf-8") as f:
-            for line in f:
-                data = json.loads(line)
-                yield key, data
-                key += 1
-