update

.gitignore

@@ -1 +1,2 @@
 SubjQA
+data/processed/default.train.jsonl

generate_reference_files.py

@@ -0,0 +1,15 @@
+import os
+from datasets import load_dataset
+
+os.makedirs('./reference_files', exist_ok=True)
+
+
+for split in ['validation', 'test']:
+    dataset = load_dataset('asahi417/qg_newsqa', '', split=split)
+    for data in ['question', 'answer', 'sentence', 'paragraph']:
+        with open('./reference_files/{}-{}.txt'.format(data, split), 'w') as f:
+            if data == 'paragraph':
+                f.write('\n'.join(dataset['paragraph_id']))
+            else:
+                f.write('\n'.join(dataset[data]))
+

process.py

@@ -2,16 +2,12 @@
 You need to run `python -m spacy download en_core_web_sm`.
 Split when uploading to dataset hub by
 ```
-gsplit -l 600 -d --additional-suffix=.jsonl test.jsonl test
-gsplit -l 600 -d --additional-suffix=.jsonl train.jsonl train
-gsplit -l 600 -d --additional-suffix=.jsonl valid.jsonl valid
+gsplit -l 1500 -d --additional-suffix=.jsonl default.train.jsonl default.train
 ```
 """
 import json
 import os
 import re
-from tqdm import tqdm
-from itertools import chain
 
 import pandas as pd
 import spacy
@@ -111,4 +107,10 @@ if __name__ == '__main__':
             with open(f'./data/processed/{i}.{s.replace(".csv", ".jsonl")}', 'w') as f:
                 f.write('\n'.join([json.dumps(i) for i in output]))
 
-
+    # for s in ["dev", "test", "train"]:
+    #     output = []
+    #     for i in ["books", "electronics", "grocery", "movies", "restaurants", "tripadvisor"]:
+    #         with open(f'./data/processed/{i}.{s}.jsonl', 'r') as f:
+    #             output += [json.loads(i) for i in f.read().split('\n') if len(i) > 0]
+    #     with open(f'./data/processed/default.{s}.jsonl', 'w') as f:
+    #         f.write('\n'.join([json.dumps(i) for i in output]))

qg_subjqa.py

@@ -20,7 +20,8 @@ class QGSubjQAConfig(datasets.BuilderConfig):
 
 class QGSubjQA(datasets.GeneratorBasedBuilder):
 
-    BUILDER_CONFIGS = [QGSubjQAConfig(name=i, description="SubjQA from domain of `{}`.".format(i)) for i in _DOMAINS]
+    BUILDER_CONFIGS = [QGSubjQAConfig(name="default", description="SubjQA from all domain of `{}`.")]
+    BUILDER_CONFIGS += [QGSubjQAConfig(name=i, description=f"SubjQA from domain of `{i}`.") for i in _DOMAINS]
 
     def _info(self):
         return datasets.DatasetInfo(
@@ -44,15 +45,22 @@ class QGSubjQA(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        downloaded_file = dl_manager.download_and_extract({
-            'train': f"{_URL}/{self.config.name}.train.jsonl",
-            'dev': f"{_URL}/{self.config.name}.dev.jsonl",
-            'test': f"{_URL}/{self.config.name}.test.jsonl"
-        })
+        if self.config.name == 'default':
+            downloaded_file = dl_manager.download_and_extract({
+                'train': [f"{_URL}/{i}.train.jsonl" for i in _DOMAINS],
+                'dev': [f"{_URL}/{i}.dev.jsonl" for i in _DOMAINS],
+                'test': [f"{_URL}/{i}.test.jsonl" for i in _DOMAINS]
+            })
+        else:
+            downloaded_file = dl_manager.download_and_extract({
+                'train': f"{_URL}/{self.config.name}.train.jsonl",
+                'dev': f"{_URL}/{self.config.name}.dev.jsonl",
+                'test': f"{_URL}/{self.config.name}.test.jsonl"
+            })
         return [
             datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_file["train"]}),
             datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepaths": downloaded_file["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepaths": downloaded_file["test"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepaths": downloaded_file["test"]})
         ]
 
     def _generate_examples(self, filepaths):