update

.gitattributes

@@ -35,3 +35,15 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.mp3 filter=lfs diff=lfs merge=lfs -text
 *.ogg filter=lfs diff=lfs merge=lfs -text
 *.wav filter=lfs diff=lfs merge=lfs -text
+data/processed/nyt.train.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/reddit.test.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/reddit.train.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/amazon.test.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/amazon.validation.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/new_wiki.test.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/new_wiki.validation.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/reddit.validation.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/amazon.train.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/new_wiki.train.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/nyt.test.jsonl filter=lfs diff=lfs merge=lfs -text
+data/processed/nyt.validation.jsonl filter=lfs diff=lfs merge=lfs -text

data/processed/amazon.test.jsonl

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data/processed/amazon.train.jsonl

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data/processed/amazon.validation.jsonl

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data/processed/new_wiki.train.jsonl

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data/processed/nyt.test.jsonl

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data/processed/nyt.validation.jsonl

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data/processed/reddit.test.jsonl

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data/processed/reddit.train.jsonl

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data/processed/reddit.validation.jsonl

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generate_reference_files.py

@@ -6,12 +6,11 @@ dataset_name = 'asahi417/qg_squadshifts'
 os.makedirs('./reference_files', exist_ok=True)
 
 
-for split in ['test']:
+for split in ['test', 'validation']:
     for domain in ["default", 'new_wiki', 'nyt', 'reddit', 'amazon']:
         dataset = load_dataset(dataset_name, domain, split=split)
         for data in ['question', 'answer', 'sentence', 'paragraph']:
             with open('./reference_files/{}-{}.{}txt'.format(data, split, "" if domain == 'default' else f"{domain}."), 'w') as f:
-
                 if data == 'paragraph':
                     tmp_data = dataset['paragraph_id']
                 else:

process.py

@@ -13,14 +13,16 @@ rm -rf amazon.test.jsonl
 import json
 import os
 import re
-import spacy
-
+from random import shuffle, seed
 from tqdm import tqdm
+
+import spacy
 from datasets import load_dataset
 
 DATASET_NAME = "squadshifts"
 DATASET_TYPES = ['new_wiki', 'nyt', 'reddit', 'amazon']
 HIGHLIGHT_TOKEN = '<hl>'
+GENERATE_TEST_SPLIT = True
 SPLITTER = spacy.load('en_core_web_sm')
 
 
@@ -88,19 +90,46 @@ if __name__ == '__main__':
     os.makedirs(output, exist_ok=True)
     for data_type in DATASET_TYPES:
         dataset = load_dataset(DATASET_NAME, data_type)
-        for _split in dataset.keys():
-            tmp_dataset = dataset[_split]
-            with open(f'{output}/{data_type}.{_split}.jsonl', 'w') as f:
-                for single_data in tqdm(tmp_dataset):
-                    question_str = single_data['question']  #.replace("\n", ".").replace('"', "'")
-                    paragraph_str = single_data['context']  #.replace("\n", ".").replace('"', "'")
-                    answer_str = single_data['answers']['text']
-                    if type(answer_str) == list:
-                        answer_str = answer_str[0]
-                    # answer_str = answer_str.replace("\n", ".").replace('"', "'")
-                    assert type(answer_str) is str, answer_str
-                    assert type(question_str) is str, question_str
-                    assert type(paragraph_str) is str, paragraph_str
-                    tmp_data = process_single_data(question=question_str, paragraph=paragraph_str, answer=answer_str)
-                    tmp_data['paragraph_id'] = single_data['id']
-                    f.write(json.dumps(tmp_data) + '\n')
+        _split = 'test'
+        tmp_dataset = dataset[_split]
+        full_data = []
+        for single_data in tqdm(tmp_dataset):
+            question_str = single_data['question']  #.replace("\n", ".").replace('"', "'")
+            paragraph_str = single_data['context']  #.replace("\n", ".").replace('"', "'")
+            answer_str = single_data['answers']['text']
+            if type(answer_str) == list:
+                answer_str = answer_str[0]
+            assert type(answer_str) is str, answer_str
+            assert type(question_str) is str, question_str
+            assert type(paragraph_str) is str, paragraph_str
+            tmp_data = process_single_data(question=question_str, paragraph=paragraph_str, answer=answer_str)
+            tmp_data['paragraph_id'] = single_data['id']
+            full_data.append(tmp_data)
+
+        # split test into train/valid/test
+        test_size = int(len(full_data)/2)
+        train_size = int((len(full_data) - test_size) * 2/3)
+        valid_size = len(full_data) - train_size - test_size
+        assert train_size + test_size + valid_size == len(full_data), f"{train_size}, {test_size}, {valid_size}"
+        paragraph_ids = list(set([i['paragraph_id'] for i in full_data]))
+        data_dict = {p: [i for i in full_data if i['paragraph_id'] == p] for p in paragraph_ids}
+        seed(0)
+        shuffle(paragraph_ids)
+        lines_train = []
+        lines_test = []
+        lines_valid = []
+
+        for i in paragraph_ids:
+            if len(lines_test) < test_size:
+                lines_test += data_dict[i]
+            elif len(lines_train) < train_size:
+                lines_train += data_dict[i]
+            else:
+                lines_valid += data_dict[i]
+        print(f'STATS(train/valid/test): {data_type}| {len(lines_train)}/{len(lines_valid)}/{len(lines_test)}')
+        with open(f'{output}/{data_type}.test.jsonl', 'w') as f:
+            f.write('\n'.join([json.dumps(i) for i in lines_test]))
+        with open(f'{output}/{data_type}.train.jsonl', 'w') as f:
+            f.write('\n'.join([json.dumps(i) for i in lines_train]))
+        with open(f'{output}/{data_type}.validation.jsonl', 'w') as f:
+            f.write('\n'.join([json.dumps(i) for i in lines_train]))

qg_squadshifts.py

@@ -6,14 +6,45 @@ import datasets
 logger = datasets.logging.get_logger(__name__)
 _DESCRIPTION = """[SQuAD Shifts](https://modestyachts.github.io/squadshifts-website/index.html) dataset for question generation (QG) task."""
 _URL = 'https://huggingface.co/datasets/asahi417/qg_squadshift/raw/main/data/processed'
+# _FILES = {
+#     str(datasets.Split.TEST): {
+#             'new_wiki': [f'{_URL}/new_wiki.test{i:02d}.jsonl' for i in range(6)],
+#             'nyt': [f'{_URL}/nyt.test{i:02d}.jsonl' for i in range(7)],
+#             'reddit': [f'{_URL}/reddit.test{i:02d}.jsonl' for i in range(7)],
+#             'amazon': [f'{_URL}/amazon.test{i:02d}.jsonl' for i in range(7)]
+#         },
+#     str(datasets.Split.TRAIN): {
+#             'new_wiki': [f'{_URL}/new_wiki.train{i:02d}.jsonl' for i in range(6)],
+#             'nyt': [f'{_URL}/nyt.train{i:02d}.jsonl' for i in range(7)],
+#             'reddit': [f'{_URL}/reddit.train{i:02d}.jsonl' for i in range(7)],
+#             'amazon': [f'{_URL}/amazon.train{i:02d}.jsonl' for i in range(7)]
+#         },
+#     str(datasets.Split.VALIDATION): {
+#             'new_wiki': [f'{_URL}/new_wiki.validation{i:02d}.jsonl' for i in range(6)],
+#             'nyt': [f'{_URL}/nyt.validation{i:02d}.jsonl' for i in range(7)],
+#             'reddit': [f'{_URL}/reddit.validation{i:02d}.jsonl' for i in range(7)],
+#             'amazon': [f'{_URL}/amazon.validation{i:02d}.jsonl' for i in range(7)]
+#         },
+# }
 _FILES = {
-    str(datasets.Split.TEST):
-        {
-            'new_wiki': [f'{_URL}/new_wiki.test{i:02d}.jsonl' for i in range(6)],
-            'nyt': [f'{_URL}/nyt.test{i:02d}.jsonl' for i in range(7)],
-            'reddit': [f'{_URL}/reddit.test{i:02d}.jsonl' for i in range(7)],
-            'amazon': [f'{_URL}/amazon.test{i:02d}.jsonl' for i in range(7)]
-        }
+    str(datasets.Split.TEST): {
+            'new_wiki': [f'{_URL}/new_wiki.test.jsonl'],
+            'nyt': [f'{_URL}/nyt.test.jsonl'],
+            'reddit': [f'{_URL}/reddit.test.jsonl'],
+            'amazon': [f'{_URL}/amazon.test.jsonl']
+        },
+    str(datasets.Split.TRAIN): {
+            'new_wiki': [f'{_URL}/new_wiki.train.jsonl'],
+            'nyt': [f'{_URL}/nyt.train.jsonl'],
+            'reddit': [f'{_URL}/reddit.train.jsonl'],
+            'amazon': [f'{_URL}/amazon.train.jsonl']
+        },
+    str(datasets.Split.VALIDATION): {
+            'new_wiki': [f'{_URL}/new_wiki.validation.jsonl'],
+            'nyt': [f'{_URL}/nyt.validation.jsonl'],
+            'reddit': [f'{_URL}/reddit.validation.jsonl'],
+            'amazon': [f'{_URL}/amazon.validation.jsonl']
+        },
 }
 _DOMAIN = list(_FILES[list(_FILES.keys())[0]].keys())