chaged loading script

GraySpectrogram.py

@@ -34,14 +34,126 @@ Using for Project Learning...
 # DatasetInfo : https://huggingface.co/docs/datasets/package_reference/main_classes
 
 
+# データを整理？
+dl_manager = DownloadManager()
+hfh_dataset_info = HfApi().dataset_info(_NAME, revision=_REVISION, timeout=100.0)
+
+# メタデータであるjsonlファイルのURLを取得
+# ここの抽出方法変えられないかな？
+train_metadata_url = DataFilesDict.from_hf_repo(
+    {datasets.Split.TRAIN: ["data/train/**"]},
+    dataset_info=hfh_dataset_info,
+    allowed_extensions=["jsonl", ".jsonl"],
+)
+
+test_metadata_url = DataFilesDict.from_hf_repo(
+    {datasets.Split.TEST: ["data/test/**"]},
+    dataset_info=hfh_dataset_info,
+    allowed_extensions=["jsonl", ".jsonl"],
+)
+        
+
+metadata_urls = dict()
+metadata_urls["train"] = train_metadata_url["train"]
+metadata_urls["test"] = test_metadata_url["test"]
+
+# 画像データは**.zipのURLをDict型として取得？
+# **.zipのURLをDict型として取得？
+train_data_url = DataFilesDict.from_hf_repo(
+    {datasets.Split.TRAIN: ["data/train/**"]},
+    dataset_info=hfh_dataset_info,
+    allowed_extensions=["zip", ".zip"],
+)
+
+test_data_url = DataFilesDict.from_hf_repo(
+    {datasets.Split.TEST: ["data/test/**"]},
+    dataset_info=hfh_dataset_info,
+    allowed_extensions=["zip", ".zip"]
+)
+data_urls = dict()
+data_urls["train"] = train_data_url["train"]
+data_urls["test"] = test_data_url["test"]
+
+class GraySpectrogramConfig(datasets.BuilderConfig):
+    """BuilderConfig for Imagette."""
+
+    def __init__(self, data_url, metadata_urls, **kwargs):
+        """BuilderConfig for Imagette.
+        Args:
+          data_url: `string`, url to download the zip file from.
+          matadata_urls: dictionary with keys 'train' and 'validation' containing the archive metadata URLs
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(GraySpectrogramConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
+        self.data_url = data_url
+        self.metadata_urls = metadata_urls
 
 class GraySpectrogram2(datasets.GeneratorBasedBuilder):
 
     # データのサブセットはここで用意
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(
-            name="train",
+            name="data 0-200",
             description=_DESCRIPTION,
+            data_url = {
+                "train" : data_urls["train"][0],
+                "test" : data_urls["test"][0]
+            },
+            metadata_urls = {
+                "train" : metadata_urls["train"][0],
+                "test" : metadata_urls["test"][0]
+            }
+            
+        ), 
+        datasets.BuilderConfig(
+            name="data 200-600",
+            description=_DESCRIPTION,
+            data_url ={
+                "train" : data_urls["train"][1],
+                "test" : data_urls["test"][1]
+            },
+            metadata_urls = {
+                "train": metadata_urls["train"][1],
+                "test" : metadata_urls["test"][1] 
+            }
+            
+        ), 
+        datasets.BuilderConfig(
+            name="data 600-1000",
+            description=_DESCRIPTION,
+            data_url = {
+                "train" : data_urls["train"][2],
+                "test" : data_urls["test"][2]
+            },
+            metadata_urls = {
+                "train" : metadata_urls["train"][2],
+                "test" : metadata_urls["test"][2]
+            }
+        ), 
+        datasets.BuilderConfig(
+            name="data 1000-1300",
+            description=_DESCRIPTION,
+            data_url = {
+                "train" : data_urls["train"][3],
+                "test" : data_urls["test"][3]
+            },
+            metadata_urls = {
+                "train" : metadata_urls["train"][3],
+                "test" : metadata_urls["test"][3]
+            }
+            
+        ), 
+        datasets.BuilderConfig(
+            name="data 1300-1600",
+            description=_DESCRIPTION,
+            data_url = {
+                "train" : data_urls["train"][4],
+                "test" : data_urls["test"][4]
+            },
+            metadata_urls = {
+                "train" : metadata_urls["train"][4],
+                "test" : metadata_urls["test"][4]
+            }   
         )
     ]
 
@@ -78,85 +190,92 @@ class GraySpectrogram2(datasets.GeneratorBasedBuilder):
       )
 
     def _split_generators(self, dl_manager: DownloadManager):
-        # huggingfaceのディレクトリからデータを取ってくる
-        hfh_dataset_info = HfApi().dataset_info(_NAME, revision=_REVISION, timeout=100.0)
-
-        # メタデータであるjsonlファイルのURLを取得
-        # ここの抽出方法変えられないかな？
-        train_metadata_url = DataFilesDict.from_hf_repo(
-            {datasets.Split.TRAIN: ["data/train/**"]},
-            dataset_info=hfh_dataset_info,
-            allowed_extensions=["jsonl", ".jsonl"],
-        )
 
-        test_metadata_url = DataFilesDict.from_hf_repo(
-            {datasets.Split.TEST: ["data/test/**"]},
-            dataset_info=hfh_dataset_info,
-            allowed_extensions=["jsonl", ".jsonl"],
-        )
+        metadata_paths = dl_manager.download(self.config.metadata_urls)
+        data_paths = dl_manager.download(self.config.data_urls)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "images": dl_manager.iter_archive(data_paths["train"]),
+                    "metadata_path": metadata_paths["train"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "images": dl_manager.iter_archive(data_paths["test"]),
+                    "metadata_path": metadata_paths["test"],
+                }
+            ),
+        ]
+
+        # # huggingfaceのディレクトリからデータを取ってくる
+        # hfh_dataset_info = HfApi().dataset_info(_NAME, revision=_REVISION, timeout=100.0)
+
+        # # メタデータであるjsonlファイルのURLを取得
+        # # ここの抽出方法変えられないかな？
+        # train_metadata_url = DataFilesDict.from_hf_repo(
+        #     {datasets.Split.TRAIN: ["data/train/**"]},
+        #     dataset_info=hfh_dataset_info,
+        #     allowed_extensions=["jsonl", ".jsonl"],
+        # )
+
+        # test_metadata_url = DataFilesDict.from_hf_repo(
+        #     {datasets.Split.TEST: ["data/test/**"]},
+        #     dataset_info=hfh_dataset_info,
+        #     allowed_extensions=["jsonl", ".jsonl"],
+        # )
         
-        metadata_urls = dict()
-        metadata_urls["train"] = train_metadata_url["train"]
-        metadata_urls["test"] = test_metadata_url["test"]
-
-        # 画像データは**.zipのURLをDict型として取得？
-        # **.zipのURLをDict型として取得？
-        train_data_url = DataFilesDict.from_hf_repo(
-            {datasets.Split.TRAIN: ["data/train/**"]},
-            dataset_info=hfh_dataset_info,
-            allowed_extensions=["zip", ".zip"],
-        )
+        # metadata_urls = dict()
+        # metadata_urls["train"] = train_metadata_url["train"]
+        # metadata_urls["test"] = test_metadata_url["test"]
 
-        test_data_url = DataFilesDict.from_hf_repo(
-            {datasets.Split.TEST: ["data/test/**"]},
-            dataset_info=hfh_dataset_info,
-            allowed_extensions=["zip", ".zip"]
-        )
-        data_urls = dict()
-        data_urls["train"] = train_data_url["train"]
-        data_urls["test"] = test_data_url["test"]
+        # # 画像データは**.zipのURLをDict型として取得？
+        # # **.zipのURLをDict型として取得？
+        # train_data_url = DataFilesDict.from_hf_repo(
+        #     {datasets.Split.TRAIN: ["data/train/**"]},
+        #     dataset_info=hfh_dataset_info,
+        #     allowed_extensions=["zip", ".zip"],
+        # )
+
+        # test_data_url = DataFilesDict.from_hf_repo(
+        #     {datasets.Split.TEST: ["data/test/**"]},
+        #     dataset_info=hfh_dataset_info,
+        #     allowed_extensions=["zip", ".zip"]
+        # )
+        # data_urls = dict()
+        # data_urls["train"] = train_data_url["train"]
+        # data_urls["test"] = test_data_url["test"]
         
-        gs = []
-
-        # for split, file_list in data_urls.items():
-        #     metadata_list = metadata_urls[split]
-        #     for i, file_ in enumerate(file_list):
-        #         '''
-        #         split : "train" or "test" or "val"
-        #         files : zip files
-        #         '''
-        #         # print(file_)
-        #         # print(metadata_list[0])
-        #         # # リポジトリからダウンロードしてとりあえずキャッシュしたURLリストを取得
-        #         metadata_path = dl_manager.download_and_extract(metadata_list[i])
-        #         downloaded_files = dl_manager.download(file_)
-        #         # # 元のコードではzipファイルの中身を"filepath"としてそのまま_generate_exampleに引き渡している？
-        #         gs.append(
-        #             datasets.SplitGenerator(
-        #                 name = split,
-        #                 gen_kwargs = {
-        #                     # "images" : iter(iter_archive[split]),
-        #                     "images" : dl_manager.iter_archive(downloaded_files),
-        #                     "metadata_path": metadata_path # メタデータパスを渡す
-        #                 }
-        #             )
-        #         )
-
-        gs = []
-
-        for split, file_list in data_urls.items():
-            metadata_list = metadata_urls[split]
-            gs.append(
-                datasets.SplitGenerator(
-                    name = split,
-                    gen_kwargs = {
-                        # "images" : iter(iter_archive[split]),
-                        "images" : dl_manager.iter_archive(dl_manager.download([file_ for file_  in file_list])),
-                        "metadata_path": dl_manager.download_and_extract(metadata_list)# メタデータパスを渡す
-                    }
-                 )
-            )
-        return gs
+        # gs = []
+
+        # # for split, file_list in data_urls.items():
+        # #     metadata_list = metadata_urls[split]
+        # #     for i, file_ in enumerate(file_list):
+        # #         '''
+        # #         split : "train" or "test" or "val"
+        # #         files : zip files
+        # #         '''
+        # #         # print(file_)
+        # #         # print(metadata_list[0])
+        # #         # # リポジトリからダウンロードしてとりあえずキャッシュしたURLリストを取得
+        # #         metadata_path = dl_manager.download_and_extract(metadata_list[i])
+        # #         downloaded_files = dl_manager.download(file_)
+        # #         # # 元のコードではzipファイルの中身を"filepath"としてそのまま_generate_exampleに引き渡している？
+        # #         gs.append(
+        # #             datasets.SplitGenerator(
+        # #                 name = split,
+        # #                 gen_kwargs = {
+        # #                     # "images" : iter(iter_archive[split]),
+        # #                     "images" : dl_manager.iter_archive(downloaded_files),
+        # #                     "metadata_path": metadata_path # メタデータパスを渡す
+        # #                 }
+        # #             )
+        # #         )
+
+        # return gs
 
     
     def _generate_examples(self, images, metadata_path):