Update Persian-conversational-dataset.py

Persian-conversational-dataset.py

@@ -1,4 +1,4 @@
-# dadrah_dataset.json
+# coding=utf-8
 # persian-conversational-dataset
 """TODO(empathetic_dialogues): Add a description here."""
 
@@ -6,13 +6,23 @@
 import csv,json
 
 import datasets
+from datasets.tasks import QuestionAnsweringExtractive
 
 
+
+logger = datasets.logging.get_logger(__name__)
+
 _DESCRIPTION = """\
 persian-conversational-dataset
 """
-_URL = "https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/empatheticdialogues.tar.gz"
 
+_URL = "https://huggingface.co/datasets/Kamtera/Persian-conversational-dataset/blob/main/"
+_URLS = [
+    "dadrah_dataset.json",
+    "dadrah_dataset1-1000_10000.json",
+    "dadrah_dataset1-10000_100000.json",
+    "dadrah_dataset1-100000_276342.json",
+]
 
 class persianConversation(datasets.GeneratorBasedBuilder):
 
@@ -28,8 +38,8 @@ class persianConversation(datasets.GeneratorBasedBuilder):
                 {
                     "title": datasets.Value("string"),
                     "question": datasets.Value("string"),
-                    "answers": datasets.Value("list"),
-                    "keywords": datasets.Value("list"),
+                    "answers": datasets.Sequence(datasets.Value("string")),
+                    "keywords": datasets.Sequence(datasets.Value("string")),
                     # These are the features of your dataset like images, labels ...
                 }
             ),
@@ -37,7 +47,8 @@ class persianConversation(datasets.GeneratorBasedBuilder):
             # specify them here. They'll be used if as_supervised=True in
             # builder.as_dataset.
             supervised_keys=None,
-            # Homepage of the dataset for documentation
+            
+            
         )
 
     def _split_generators(self, dl_manager):
@@ -45,16 +56,32 @@ class persianConversation(datasets.GeneratorBasedBuilder):
         # TODO(empathetic_dialogues): Downloads the data and defines the splits
         # dl_manager is a datasets.download.DownloadManager that can be used to
         # download and extract URLs
+        downloaded_files = dl_manager.download(_URLS)
+        logger.info("| > downloaded files")
+        logger.info(downloaded_files)
         return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "files": downloaded_files[1:3],
+                    "split_file": "train",
+                },
+            ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 # These kwargs will be passed to _generate_examples
-                gen_kwargs={"files": ["dadrah_dataset.json"], "split_file": "dadrah_dataset.json"},
+                gen_kwargs={
+                    "files": downloaded_files[0],
+                    "split_file": "test"
+                },
             ),
         ]
 
     def _generate_examples(self, files, split_file):
         """Yields examples."""
+        logger.info("| > generate examples for "+split_file)
+        logger.info(files)
         for path, f in files:
             if split_file == path:
                 with open(split_file, 'r', encoding='utf-8') as fmm: