all data

MRC/ArabicaQA.py

@@ -1,3 +1,5 @@
+import csv
+import json
 from datasets import load_dataset_builder, DatasetInfo, DownloadConfig, GeneratorBasedBuilder, datasets
 
 class CustomSQuADFormatDataset(GeneratorBasedBuilder):
@@ -5,7 +7,11 @@ class CustomSQuADFormatDataset(GeneratorBasedBuilder):
 
     VERSION = datasets.Version("1.0.0")
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="ArabicaQA", version=VERSION, description="Custom dataset similar to SQuAD format.")
+        datasets.BuilderConfig(
+            name="ArabicaQA",
+            version=VERSION,
+            description="Custom dataset similar to SQuAD format, including CSV data."
+        )
     ]
 
     def _info(self):
@@ -23,6 +29,7 @@ class CustomSQuADFormatDataset(GeneratorBasedBuilder):
                             "answer_start": datasets.Value("int32"),
                         }
                     ),
+                    # Additional fields from the CSV can be added here if needed
                 }
             ),
             supervised_keys=None,
@@ -34,19 +41,27 @@ class CustomSQuADFormatDataset(GeneratorBasedBuilder):
         urls_to_download = {
             "train": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/train.json",
             "dev": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/val.json",
-            "test": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/test.json"
+            "test": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/test.json",
+            "csv": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/all_data_meta.csv"
         }
         downloaded_files = dl_manager.download(urls_to_download)
 
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["test"]}),
-
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"json_filepath": downloaded_files["train"], "csv_filepath": downloaded_files["csv"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"json_filepath": downloaded_files["dev"], "csv_filepath": downloaded_files["csv"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"json_filepath": downloaded_files["test"], "csv_filepath": downloaded_files["csv"]}),
         ]
 
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
+    def _generate_examples(self, json_filepath, csv_filepath):
+        # Read the CSV file and store it in memory
+        csv_data = {}
+        with open(csv_filepath, encoding="utf-8") as csv_file:
+            csv_reader = csv.DictReader(csv_file)
+            for row in csv_reader:
+                csv_data[row['question_id']] = row
+
+        # Read the JSON file and yield examples
+        with open(json_filepath, encoding="utf-8") as f:
             squad_data = json.load(f)["data"]
             for article in squad_data:
                 title = article.get("title", "")
@@ -56,10 +71,15 @@ class CustomSQuADFormatDataset(GeneratorBasedBuilder):
                         id_ = qa["id"]
                         question = qa["question"]
                         answers = [{"text": answer["text"], "answer_start": answer["answer_start"]} for answer in qa.get("answers", [])]
-                        
-                        yield id_, {
+
+                        # Combine data from the CSV if present
+                        additional_csv_data = csv_data.get(id_, {})
+                        # Include additional fields from the CSV in the example if necessary
+                        example = {
                             "title": title,
                             "context": context,
                             "question": question,
                             "answers": answers,
+                            # Add additional fields from the CSV here
                         }
+                        yield id_, example

arabicaqa.py

@@ -1,3 +1,5 @@
+import csv
+import json
 from datasets import load_dataset_builder, DatasetInfo, DownloadConfig, GeneratorBasedBuilder, datasets
 
 class CustomSQuADFormatDataset(GeneratorBasedBuilder):
@@ -5,9 +7,12 @@ class CustomSQuADFormatDataset(GeneratorBasedBuilder):
 
     VERSION = datasets.Version("1.0.0")
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="ArabicaQA", version=VERSION, description="Custom dataset similar to SQuAD format.")
+        datasets.BuilderConfig(
+            name="ArabicaQA",
+            version=VERSION,
+            description="Custom dataset similar to SQuAD format, including CSV data."
+        )
     ]
-    
 
     def _info(self):
         return DatasetInfo(
@@ -24,6 +29,7 @@ class CustomSQuADFormatDataset(GeneratorBasedBuilder):
                             "answer_start": datasets.Value("int32"),
                         }
                     ),
+                    # Additional fields from the CSV can be added here if needed
                 }
             ),
             supervised_keys=None,
@@ -35,19 +41,27 @@ class CustomSQuADFormatDataset(GeneratorBasedBuilder):
         urls_to_download = {
             "train": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/train.json",
             "dev": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/val.json",
-            "test": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/test.json"
+            "test": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/test.json",
+            "csv": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/all_data_meta.csv"
         }
         downloaded_files = dl_manager.download(urls_to_download)
 
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["test"]}),
-
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"json_filepath": downloaded_files["train"], "csv_filepath": downloaded_files["csv"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"json_filepath": downloaded_files["dev"], "csv_filepath": downloaded_files["csv"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"json_filepath": downloaded_files["test"], "csv_filepath": downloaded_files["csv"]}),
         ]
 
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
+    def _generate_examples(self, json_filepath, csv_filepath):
+        # Read the CSV file and store it in memory
+        csv_data = {}
+        with open(csv_filepath, encoding="utf-8") as csv_file:
+            csv_reader = csv.DictReader(csv_file)
+            for row in csv_reader:
+                csv_data[row['question_id']] = row
+
+        # Read the JSON file and yield examples
+        with open(json_filepath, encoding="utf-8") as f:
             squad_data = json.load(f)["data"]
             for article in squad_data:
                 title = article.get("title", "")
@@ -57,10 +71,15 @@ class CustomSQuADFormatDataset(GeneratorBasedBuilder):
                         id_ = qa["id"]
                         question = qa["question"]
                         answers = [{"text": answer["text"], "answer_start": answer["answer_start"]} for answer in qa.get("answers", [])]
-                        
-                        yield id_, {
+
+                        # Combine data from the CSV if present
+                        additional_csv_data = csv_data.get(id_, {})
+                        # Include additional fields from the CSV in the example if necessary
+                        example = {
                             "title": title,
                             "context": context,
                             "question": question,
                             "answers": answers,
+                            # Add additional fields from the CSV here
                         }
+                        yield id_, example