Upload aftdb.py

aftdb.py

@@ -58,7 +58,7 @@ class AFT_Dataset(datasets.GeneratorBasedBuilder):
                 "Dataset containing scientific article figures associated "
                 "with their caption, summary, and article title."
             ),
-            data_dir="./{type}",
+            data_dir="./data/arxiv_dataset/{type}", # A modiféer sur Huggingface Hub
             nb_files_figure=_NB_TAR_FIGURE,
             nb_files_table=None
         ),
@@ -70,7 +70,7 @@ class AFT_Dataset(datasets.GeneratorBasedBuilder):
                 "representation of the table, including its caption, summary, "
                 "and article title."
             ),
-            data_dir="./{type}",
+            data_dir="./data/arxiv_dataset/{type}", # A modiféer sur Huggingface Hub
             nb_files_figure=None,
             nb_files_table=_NB_TAR_TABLE
         ),
@@ -82,7 +82,7 @@ class AFT_Dataset(datasets.GeneratorBasedBuilder):
                 "textual representation of the table, including its caption, "
                 "summary, and article title."
             ),
-            data_dir="./{type}",
+            data_dir="./data/arxiv_dataset/{type}", # A modiféer sur Huggingface Hub
             nb_files_figure=_NB_TAR_FIGURE,
             nb_files_table=_NB_TAR_TABLE
         )
@@ -135,57 +135,32 @@ class AFT_Dataset(datasets.GeneratorBasedBuilder):
                 data_dir=self.config.data_dir.format(type='table'),
                 nb_files=self.config.nb_files_table
             )
-        dataset = []
         if dl_manager.is_streaming:
             downloaded_files = dl_manager.download(all_path)
-            dataset.append(
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    gen_kwargs={
-                        'filepaths': [
-                            dl_manager.iter_archive(ii)
-                            for ii in downloaded_files['train']
-                        ],
-                        'is_streaming': dl_manager.is_streaming
-                    }
-                )
-            )
-            dataset.append(
-                datasets.SplitGenerator(
-                    name=datasets.Split.TEST,
-                    gen_kwargs={
-                        "filepaths": [
-                            dl_manager.iter_archive(ii)
-                            for ii in downloaded_files['test']
-                        ],
-                        'is_streaming': dl_manager.is_streaming
-                    }
-                )
-            )
+            downloaded_files['train'] = [
+                dl_manager.iter_archive(ii) for ii in downloaded_files['train']
+            ]
+            downloaded_files['test'] = [
+                dl_manager.iter_archive(ii) for ii in downloaded_files['test']
+            ]
         else:
-            dataset.append(
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    gen_kwargs={
-                        'filepaths': dl_manager.download_and_extract(
-                            all_path['train']
-                        ),
-                        'is_streaming': dl_manager.is_streaming
-                    }
-                )
-            )
-            dataset.append(
-                datasets.SplitGenerator(
-                    name=datasets.Split.TEST,
-                    gen_kwargs={
-                        "filepaths": dl_manager.download_and_extract(
-                            all_path['test']
-                        ),
-                        'is_streaming': dl_manager.is_streaming
-                    }
-                )
+            downloaded_files = dl_manager.download_and_extract(all_path)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    'filepaths': downloaded_files['train'],
+                    'is_streaming': dl_manager.is_streaming
+                }
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepaths": downloaded_files['test'],
+                    'is_streaming': dl_manager.is_streaming
+                }
             )
-        return dataset
+        ]
 
     def _generate_examples(self, filepaths, is_streaming):
         if is_streaming: