update the running script

Controlled-Text-Reduction-dataset.py

@@ -1,242 +1,3 @@
-# # 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.
-# """A Dataset loading script for the Controlled Text Reduction dataset."""
-
-
-# import datasets
-# from dataclasses import dataclass
-# from pathlib import Path
-# from typing import List, Tuple
-# import pandas as pd
-# import json
-# import gzip
-# import itertools
-
-
-# _CITATION = """"""
-# # _CITATION = """\
-# # @inproceedings{roit2020controlled,
-# #   title={Controlled Crowdsourcing for High-Quality QA-SRL Annotation},
-# #   author={Roit, Paul and Klein, Ayal and Stepanov, Daniela and Mamou, Jonathan and Michael, Julian and Stanovsky, Gabriel and Zettlemoyer, Luke and Dagan, Ido},
-# #   booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
-# #   pages={7008--7013},
-# #   year={2020}
-# # }
-# # """
-
-
-# _DESCRIPTION = """\
-# The dataset contains document-summary pairs with document spans (referred to as "highlights"), indicating the "pre-selected" spans that lead to the creation of the summary.
-# The evaluation and test datasets were constructed via controlled crowdsourcing.
-# The train datasets were automatically generated using the summary-source proposition-level alignment model SuperPAL (Ernst et al., 2021).
-# """
-
-# _HOMEPAGE = "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main"
-
-# _LICENSE = """MIT License
-# Copyright (c) 2022 lovodkin93
-# Permission is hereby granted, free of charge, to any person obtaining a copy
-# of this software and associated documentation files (the "Software"), to deal
-# in the Software without restriction, including without limitation the rights
-# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-# copies of the Software, and to permit persons to whom the Software is
-# furnished to do so, subject to the following conditions:
-# The above copyright notice and this permission notice shall be included in all
-# copies or substantial portions of the Software.
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-# SOFTWARE."""
-
-
-# # _URLs = {
-# #     "csv": {
-# #         "sentences": {
-# #             "wikinews.dev": "https://github.com/plroit/qasrl-gs/raw/master/data/sentences/wikinews.dev.full.csv",
-# #             "wikinews.test": "https://github.com/plroit/qasrl-gs/raw/master/data/sentences/wikinews.test.full.csv",
-# #             "wikipedia.dev": "https://github.com/plroit/qasrl-gs/raw/master/data/sentences/wikipedia.dev.full.csv",
-# #             "wikipedia.test": "https://github.com/plroit/qasrl-gs/raw/master/data/sentences/wikipedia.test.full.csv",
-# #         },
-# #         "qasrl-annotations": {
-# #             "wikinews.dev": "https://github.com/plroit/qasrl-gs/raw/master/data/gold/wikinews.dev.gold.csv",
-# #             "wikinews.test": "https://github.com/plroit/qasrl-gs/raw/master/data/gold/wikinews.test.gold.csv",
-# #             "wikipedia.dev": "https://github.com/plroit/qasrl-gs/raw/master/data/gold/wikipedia.dev.gold.csv",
-# #             "wikipedia.test": "https://github.com/plroit/qasrl-gs/raw/master/data/gold/wikipedia.test.gold.csv",
-# #         }, 
-# #     },
-# #     "jsonl": "https://qasrl.org/data/qasrl-gs.tar"       
-# # }
-
-# _URLs = {
-#     "DUC-2001-2002": {
-#         "dev": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/dev_DUC-2001-2002.csv",
-#         "test": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/test_DUC-2001-2002.csv",
-#         "train": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/train_DUC-2001-2002.csv"
-#     },  
-#     "CNN-DM": {
-#         "train": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/train_CNNDM.csv",
-#         "dev": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/dev_DUC-2001-2002.csv",
-#         "test": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/test_DUC-2001-2002.csv",
-#     },    
-# }
-
-
-# @dataclass
-# class ControlledTextReductionConfig(datasets.BuilderConfig):
-#     """ Allow the loader to re-distribute the original dev and test splits between train, dev and test. """
-#     data_source: str = "DUC-2001-2002" # "DUC-2001-2002" or "CNN-DM"
-
-
-
-# class ControlledTextReduction(datasets.GeneratorBasedBuilder):
-#     """Controlled Text Reduction: dataset for the Controlled Text Reduction task ().
-#     Each data point consists of a document, a summary, and a list of spans of the document that are the pre-selected content whose summary is the summary"""
-
-
-#     VERSION = datasets.Version("1.0.0")
-
-#     BUILDER_CONFIG_CLASS = ControlledTextReductionConfig
-
-#     BUILDER_CONFIGS = [
-#         ControlledTextReductionConfig(
-#             name="DUC-2001-2002", 
-#             version=VERSION, 
-#             description="This provides the Controlled Text Reduction dataset extracted from the DUC 2001-2002 Single Document Summarization benchmark",
-#             data_source="DUC-2001-2002"
-#         ),
-#         ControlledTextReductionConfig(
-#             name="CNN-DM", 
-#             version=VERSION, 
-#             description="This provides the Controlled Text Reduction dataset extracted from the CNN-DM dataset (the train split)",
-#             data_source="CNN-DM"
-#         )
-#     ]
-
-#     DEFAULT_CONFIG_NAME = (
-#         "DUC-2001-2002"  # It's not mandatory to have a default configuration. Just use one if it make sense.
-#     )
-
-#     def _info(self):
-#         features = datasets.Features(
-#             {
-#                 "doc_text": datasets.Value("string"),
-#                 "summary_text": datasets.Value("string"),
-#                 "highlight_spans": 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: datasets.utils.download_manager.DownloadManager):
-#         """Returns SplitGenerators."""            
-        
-#         URLs = _URLs[self.config.data_source]
-#         # Download and prepare all files - keep same structure as URLs 
-#         corpora = {section:  Path(dl_manager.download_and_extract(URLs[section])) 
-#                    for section in URLs} 
-        
-#         if self.config.data_source=="CNN-DM":
-#             return [
-#                 datasets.SplitGenerator(
-#                     name=datasets.Split.TRAIN,
-#                     # These kwargs will be passed to _generate_examples
-#                     gen_kwargs={
-#                         "filepath": corpora["train"]
-#                     },
-#                 ),
-#                 datasets.SplitGenerator(
-#                     name=datasets.Split.VALIDATION,
-#                     # These kwargs will be passed to _generate_examples
-#                     gen_kwargs={
-#                         "filepath": corpora["dev"]
-#                     },
-#                 ),
-#                 datasets.SplitGenerator(
-#                     name=datasets.Split.TEST,
-#                     # These kwargs will be passed to _generate_examples
-#                     gen_kwargs={
-#                         "filepath": corpora["test"]
-#                     },
-#                 ),
-#             ]
-
-#         else:
-#             return [
-#                 datasets.SplitGenerator(
-#                     name=datasets.Split.TRAIN,
-#                     # These kwargs will be passed to _generate_examples
-#                     gen_kwargs={
-#                         "filepath": corpora["train"]
-#                     },
-#                 ),
-#                 datasets.SplitGenerator(
-#                     name=datasets.Split.VALIDATION,
-#                     # These kwargs will be passed to _generate_examples
-#                     gen_kwargs={
-#                         "filepath": corpora["dev"]
-#                     },
-#                 ),
-#                 datasets.SplitGenerator(
-#                     name=datasets.Split.TEST,
-#                     # These kwargs will be passed to _generate_examples
-#                     gen_kwargs={
-#                         "filepath": corpora["test"]
-#                     },
-#                 ),
-#             ]
-    
-#     def _generate_examples(self, filepath: List[str]):
-
-#         """ Yields Controlled Text Reduction examples from a csv file. Each instance contains the document, the summary and the pre-selected spans."""
-
-#         # merge annotations from sections 
-#         df = pd.read_csv(filepath, index_col=False)
-#         for counter, dic in enumerate(df.to_dict('records')):
-#             columns_to_load_into_object = ["doc_text", "summary_text", "highlight_spans"]
-#             for key in columns_to_load_into_object:
-#                 dic[key] = eval(dic[key])
-#             yield counter, dic
-
-
-
-
-
-#################################################################################################################################################
-
-
-
-
-
-
 # coding=utf-8
 # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
 #
@@ -313,29 +74,6 @@ _URLs = {
     },    
 }
 
-# _URLs = {
-#         "dev_DUC-2001-2002": "https://media.githubusercontent.com/media/lovodkin93/Controlled_Text_Reduction/main/data/dev_DUC-2001-2002.csv",
-#         "test_DUC-2001-2002": "https://media.githubusercontent.com/media/lovodkin93/Controlled_Text_Reduction/main/data/test_DUC-2001-2002.csv",
-#         "train_DUC-2001-2002": "https://media.githubusercontent.com/media/lovodkin93/Controlled_Text_Reduction/main/data/train_DUC-2001-2002.csv"   
-# }
-
-
-COLUMNS = ["doc_text", "summary_text", "highlight_spans"]
-
-
-# _URLs = {
-#     "DUC-2001-2002": {
-#         "dev": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/dev_DUC-2001-2002.csv",
-#         "test": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/test_DUC-2001-2002.csv",
-#         "train": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/train_DUC-2001-2002.csv"
-#     },  
-#     "CNN-DM": {
-#         "train": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/train_CNNDM.csv",
-#         "dev": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/dev_DUC-2001-2002.csv",
-#         "test": "https://github.com/lovodkin93/Controlled_Text_Reduction/tree/main/data/test_DUC-2001-2002.csv",
-#     },    
-# }
-
 
 @dataclass
 class ControlledTextReductionConfig(datasets.BuilderConfig):
@@ -444,22 +182,6 @@ class ControlledTectReduction(datasets.GeneratorBasedBuilder):
                     ),
                 ]
 
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     def _generate_examples(self, filepath: List[str]):
 
@@ -468,7 +190,4 @@ class ControlledTectReduction(datasets.GeneratorBasedBuilder):
         # merge annotations from sections 
         df = pd.read_csv(filepath)
         for counter, dic in enumerate(df.to_dict('records')):
-            columns_to_load_into_object = ["doc_text", "summary_text", "highlight_spans"]
-            # for key in columns_to_load_into_object:
-            #     dic[key] = eval(dic[key])
             yield counter, dic