support datadir

unit-test_PDFfolder.py

@@ -12,49 +12,59 @@ _DESCRIPTION = "A generic pdf folder"
 class PdfFolder(datasets.GeneratorBasedBuilder):
     def _info(self):
 
-        folder=None
-        if isinstance(self.config.data_files, str):
+        folder = None
+        if isinstance(self.config.data_dir, str):
+            folder = self.config.data_dir
+        elif isinstance(self.config.data_files, str):
             folder = self.config.data_files
         elif isinstance(self.config.data_files, dict):
-            folder = self.config.data_files.get('train', None)
+            folder = self.config.data_files.get("train", None)
 
         if folder is None:
             raise RuntimeError()
 
-        classes = sorted([x.name.lower() for x in Path(folder).glob('*/**')]).unique()
-        
+        classes = sorted([x.name.lower() for x in Path(folder).glob("*/**")]).unique()
+
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
             features=datasets.Features(
                 {
                     "file": datasets.Sequence(datasets.Image()),
-                    "labels": datasets.features.ClassLabel(names=classes)
+                    "labels": datasets.features.ClassLabel(names=classes),
                 }
             ),
             task_templates=None,
         )
 
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+    def _split_generators(
+        self, dl_manager: datasets.DownloadManager
+    ) -> List[datasets.SplitGenerator]:
 
         data_files = self.config.data_files
 
         if isinstance(data_files, str):
-            return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'archive_path': data_files})]
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN, gen_kwargs={"archive_path": data_files}
+                )
+            ]
 
         splits = []
         for split_name, folder in data_files.items():
-            splits.append(datasets.SplitGenerator(name=split_name, gen_kwargs={'archive_path': folder}))
+            splits.append(
+                datasets.SplitGenerator(name=split_name, gen_kwargs={"archive_path": folder})
+            )
 
         return splits
 
     def _generate_examples(self, archive_path):
-        labels = self.info.features['labels']
+        labels = self.info.features["labels"]
         logger.info("generating examples from = %s", archive_path)
-        extensions = {'.pdf'}
-        for i, path in enumerate(Path(archive_path).glob('**/*')):
+        extensions = {".pdf"}
+        for i, path in enumerate(Path(archive_path).glob("**/*")):
             if path.suffix in extensions:
 
                 images = pdf2image.convert_from_bytes(path.posix())
 
-                #convert PDF to list of images
-                yield i, {'file': images, 'labels': labels.encode_example(path.parent.name.lower())}
+                # convert PDF to list of images
+                yield i, {"file": images, "labels": labels.encode_example(path.parent.name.lower())}