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IndicParaphrase.py

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-
-
-
-import json
-import os
-
-import datasets
-
-_CITATION = """\
-@inproceedings{Kumar2022IndicNLGSM,
-  title={IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages},
-  author={Aman Kumar and Himani Shrotriya and Prachi Sahu and Raj Dabre and Ratish Puduppully and Anoop Kunchukuttan and Amogh Mishra and Mitesh M. Khapra and Pratyush Kumar},
-  year={2022},
-  url = "https://arxiv.org/abs/2203.05437"
-}
-"""
-
-_DESCRIPTION = """\
-This is the paraphrasing dataset released as part of IndicNLG Suite. Each 
-input is paired with up to 5 references. We create this dataset in eleven 
-languages including as, bn, gu, hi, kn, ml, mr, or, pa, ta, te. The total
-size of the dataset is 5.57M.
-
-"""
-_HOMEPAGE = "https://indicnlp.ai4bharat.org/indicnlg-suite"
-
-_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License"
-
-_URL = "https://huggingface.co/datasets/ai4bharat/IndicParaphrase/resolve/main/data/{}_IndicParaphrase_v{}.zip"
-
-
-_LANGUAGES = [
-    "as",
-    "bn",
-    "gu",
-    "hi",
-    "kn",
-    "ml",
-    "mr",
-    "or",
-    "pa",
-    "ta",
-    "te"
-]
-    
-
-class IndicParaphrase(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-    
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="{}".format(lang),
-            version=datasets.Version("1.0.0")
-        )
-        for lang in _LANGUAGES
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "pivot": datasets.Value("string"),
-                    "input": datasets.Value("string"),
-                    "target": datasets.Value("string"),
-                    "references": [datasets.Value("string")]
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-            license=_LICENSE,
-            version=self.VERSION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        lang = str(self.config.name)
-        url = _URL.format(lang, self.VERSION.version_str[:-2])
-
-        data_dir = dl_manager.download_and_extract(url)
-        if lang == 'as' :
-            return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "test_" + lang + ".jsonl"),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "dev_" + lang + ".jsonl"),
-                },
-            ),
-        ]
-        else :
-            return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir,  "train_" + lang + ".jsonl"),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "test_" + lang + ".jsonl"),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "dev_" + lang + ".jsonl"),
-                },
-            ),
-        ]
-            
-        
-
-    def _generate_examples(self, filepath):
-        """Yields examples as (key, example) tuples."""
-        with open(filepath, encoding="utf-8") as f:
-            for idx_, row in enumerate(f):
-                data = json.loads(row)
-                yield idx_, {
-                    "id": data["id"],
-                    "pivot": data["pivot"],
-                    "input": data["input"],
-                    "target": data["target"],
-                    "references": data["references"]
-                   
-                }

README.md

@@ -1,216 +0,0 @@
----
-annotations_creators:
-- no-annotation
-language_creators:
-- found
-language:
-- as
-- bn
-- gu
-- hi
-- kn
-- ml
-- mr
-- or
-- pa
-- ta
-- te
-license:
-- cc-by-nc-4.0
-multilinguality:
-- multilingual
-pretty_name: IndicParaphrase
-size_categories:
-- 1M<n<10M
-source_datasets:
-- original
-task_categories:
-- conditional-text-generation
-task_ids:
-- conditional-text-generation-other-paraphrase-generation
----
-
-# Dataset Card for "IndicParaphrase"
-
-## Table of Contents
-- [Dataset Card Creation Guide](#dataset-card-creation-guide)
-  - [Table of Contents](#table-of-contents)
-  - [Dataset Description](#dataset-description)
-    - [Dataset Summary](#dataset-summary)
-    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-    - [Languages](#languages)
-  - [Dataset Structure](#dataset-structure)
-    - [Data Instances](#data-instances)
-    - [Data Fields](#data-fields)
-    - [Data Splits](#data-splits)
-  - [Dataset Creation](#dataset-creation)
-    - [Curation Rationale](#curation-rationale)
-    - [Source Data](#source-data)
-      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
-      - [Who are the source language producers?](#who-are-the-source-language-producers)
-    - [Annotations](#annotations)
-      - [Annotation process](#annotation-process)
-      - [Who are the annotators?](#who-are-the-annotators)
-    - [Personal and Sensitive Information](#personal-and-sensitive-information)
-  - [Considerations for Using the Data](#considerations-for-using-the-data)
-    - [Social Impact of Dataset](#social-impact-of-dataset)
-    - [Discussion of Biases](#discussion-of-biases)
-    - [Other Known Limitations](#other-known-limitations)
-  - [Additional Information](#additional-information)
-    - [Dataset Curators](#dataset-curators)
-    - [Licensing Information](#licensing-information)
-    - [Citation Information](#citation-information)
-    - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** https://indicnlp.ai4bharat.org/indicnlg-suite
-- **Paper:** [IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages](https://arxiv.org/abs/2203.05437)
-- **Point of Contact:** 
-
-### Dataset Summary
-
-IndicParaphrase is the paraphrasing dataset released as part of IndicNLG Suite. Each 
-input is paired with up to 5 references. We create this dataset in eleven 
-languages including as, bn, gu, hi, kn, ml, mr, or, pa, ta, te. The total
-size of the dataset is 5.57M. 
-
-
-### Supported Tasks and Leaderboards
-
-**Tasks:** Paraphrase generation
-
-**Leaderboards:** Currently there is no Leaderboard for this dataset.
-
-### Languages
--  `Assamese (as)`
--  `Bengali (bn)`
--  `Gujarati (gu)`
--  `Kannada (kn)`
--  `Hindi (hi)`
--  `Malayalam (ml)`
--  `Marathi (mr)`
--  `Oriya (or)`
--  `Punjabi (pa)`
--  `Tamil (ta)`
--  `Telugu (te)`
-
-## Dataset Structure
-
-### Data Instances
-
-One example from the `hi` dataset is given below in JSON format. 
-  ```
-  {
-    'id': '1',
- 'input': 'निजी क्षेत्र में प्रदेश की 75 प्रतिशत नौकरियां हरियाणा के युवाओं के लिए आरक्षित की जाएगी।',
- 'references': ['प्रदेश के युवाओं को निजी उद्योगों में 75 प्रतिशत आरक्षण देंगे।',
-  'युवाओं के लिए हरियाणा की सभी प्राइवेट नौकरियों में 75 प्रतिशत आरक्षण लागू किया जाएगा।',
-  'निजी क्षेत्र में 75 प्रतिशत आरक्षित लागू कर प्रदेश के युवाओं का रोजगार सुनिश्चत किया जाएगा।',
-  'प्राईवेट कम्पनियों में हरियाणा के नौजवानों को 75 प्रतिशत नौकरियां में आरक्षित की जाएगी।',
-  'प्रदेश की प्राइवेट फैक्टरियों में 75 फीसदी रोजगार हरियाणा के युवाओं के लिए आरक्षित किए जाएंगे।'],
- 'target': 'प्रदेश के युवाओं को निजी उद्योगों में 75 प्रतिशत आरक्षण देंगे।'
-}
-  ```
-
-### Data Fields
--  `id (string)`: Unique identifier.
--  `pivot (string)`: English sentence used as the pivot 
--  `input (string)`: Input sentence 
--  `references (list of strings)`: Paraphrases of `input`, ordered according to the least n-gram overlap
--  `target (string)`: The first reference (most dissimilar paraphrase) 
-
-
-
-### Data Splits
-
-We first select 10K instances each for the validation and test and put remaining in the training dataset. `Assamese (as)`, due to its low-resource nature, could only be split into validation and test sets with 4,420 examples each.
-Individual dataset with train-dev-test example counts are given below:
-
-
-Language      | ISO 639-1 Code |Train | Dev | Test |
---------------|----------------|-------|-----|------|
-Assamese | as | - | 4,420 | 4,420 |
-Bengali | bn | 890,445 | 10,000 | 10,000 |
-Gujarati | gu |  379,202 | 10,000 | 10,000 |
-Hindi | hi | 929,507 | 10,000 | 10,000 |
-Kannada | kn |  522,148 | 10,000 | 10,000 | 
-Malayalam | ml |761,933  | 10,000 | 10,000 | 
-Marathi | mr |406,003 | 10,000 | 10,000 | 
-Oriya | or | 105,970 | 10,000 | 10,000 | 
-Punjabi | pa |  266,704 | 10,000 | 10,000 | 
-Tamil | ta | 497,798 | 10,000 | 10,000 | 
-Telugu | te | 596,283 | 10,000 | 10,000 |
-
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More information needed]
-
-### Source Data
-
-[Samanantar dataset](https://indicnlp.ai4bharat.org/samanantar/)
-
-#### Initial Data Collection and Normalization
-
-[Detailed in the paper](https://arxiv.org/abs/2203.05437)
-
-
-#### Who are the source language producers?
-
-[Detailed in the paper](https://arxiv.org/abs/2203.05437)
-
-
-### Annotations
-[More information needed]
-#### Annotation process
-[More information needed]
-
-#### Who are the annotators?
-
-[More information needed]
-
-### Personal and Sensitive Information
-
-[More information needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More information needed]
-
-### Discussion of Biases
-
-[More information needed]
-
-### Other Known Limitations
-
-[More information needed]
-
-## Additional Information
-
-### Dataset Curators
-
-[More information needed]
-
-### Licensing Information
-
-Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
-### Citation Information
-
-If you use any of the datasets, models or code modules, please cite the following paper:
-```
-@inproceedings{Kumar2022IndicNLGSM,
-  title={IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages},
-  author={Aman Kumar and Himani Shrotriya and Prachi Sahu and Raj Dabre and Ratish Puduppully and Anoop Kunchukuttan and Amogh Mishra and Mitesh M. Khapra and Pratyush Kumar},
-  year={2022},
-  url = "https://arxiv.org/abs/2203.05437"
-}  
-```
-
-
-### Contributions
-

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