Update test.py

test.py

@@ -24,16 +24,13 @@ from itertools import repeat
 from multiprocessing import Manager, Pool, Process
 from pathlib import Path
 from shutil import copyfileobj
-import numpy as np
+
 import pandas as pd
 import requests
-from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, TypeVar, Union
-import warnings
+
 import datasets
 import urllib3
 
-
-
 urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
 
 _CITATION = """\
@@ -68,41 +65,41 @@ _URL = "https://mm.kaist.ac.kr/datasets/voxceleb"
 
 _URLS = {
     "video": {
-        "placeholder": "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_mp4_partaa",
+        "placeholder": "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_mp4_parta",
         "dev": (
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_mp4_partaa",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_mp4_partab",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_mp4_partac",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_mp4_partad",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_mp4_partae",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_mp4_partaf",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_mp4_partag",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_mp4_partah",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_mp4_partai",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_mp4_partaa",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_mp4_partab",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_mp4_partac",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_mp4_partad",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_mp4_partae",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_mp4_partaf",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_mp4_partag",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_mp4_partah",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_mp4_partai",
         ),
         "test": "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_test_mp4.zip",
     },
     "audio1": {
-        "placeholder": "hf://datasets/ProgramComputer/voxceleb/vox1/vox1_dev_wav_partaa",
+        "placeholder": "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox1/vox1_dev_wav_parta",
         "dev": (
-            "hf://datasets/ProgramComputer/voxceleb/vox1/vox1_dev_wav_partaa",
-            "hf://datasets/ProgramComputer/voxceleb/vox1/vox1_dev_wav_partab",
-            "hf://datasets/ProgramComputer/voxceleb/vox1/vox1_dev_wav_partac",
-            "hf://datasets/ProgramComputer/voxceleb/vox1/vox1_dev_wav_partad",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox1/vox1_dev_wav_partaa",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox1/vox1_dev_wav_partab",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox1/vox1_dev_wav_partac",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox1/vox1_dev_wav_partad",
         ),
         "test": "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox1/vox1_test_wav.zip",
     },
     "audio2": {
-        "placeholder": "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_aac_partaa",
+        "placeholder": "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_aac_parta",
         "dev": (
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_aac_partaa",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_aac_partab",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_aac_partac",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_aac_partad",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_aac_partae",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_aac_partaf",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_aac_partag",
-            "hf://datasets/ProgramComputer/voxceleb/vox2/vox2_dev_aac_partah",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_aac_partaa",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_aac_partab",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_aac_partac",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_aac_partad",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_aac_partae",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_aac_partaf",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_aac_partag",
+            "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_dev_aac_partah",
         ),
         "test": "https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox2/vox2_test_aac.zip",
     },
@@ -115,20 +112,8 @@ _PLACEHOLDER_MAPS = dict(
     for urls in _URLS.values()
     for value in ((urls["placeholder"], urls["dev"]), (urls["test"], (urls["test"],)))
 )
-class NestedDataStructure:
-    def __init__(self, data=None):
-        self.data = data if data is not None else []
 
-    def flatten(self, data=None):
-        data = data if data is not None else self.data
-        if isinstance(data, dict):
-            return self.flatten(list(data.values()))
-        elif isinstance(data, (list, tuple)):
-            return [flattened for item in data for flattened in self.flatten(item)]
-        else:
-            return [data]
 
-            
 def _mp_download(
     url,
     tmp_path,
@@ -153,7 +138,7 @@ def _mp_download(
             raise ConnectionError("failed to fetch dataset")
 
 
-class Test(datasets.GeneratorBasedBuilder):
+class VoxCeleb(datasets.GeneratorBasedBuilder):
     """VoxCeleb is an unlabled dataset consisting of short clips of human speech from interviews on YouTube"""
 
     VERSION = datasets.Version("1.0.0")
@@ -202,11 +187,13 @@ class Test(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
+        if dl_manager.is_streaming:
+            raise TypeError("Streaming is not supported for VoxCeleb")
         targets = (
             ["audio1", "audio2"] if self.config.name == "audio" else [self.config.name]
         )
-          
-       
+
+
         def download_custom(placeholder_url, path):
             nonlocal dl_manager
             sources = _PLACEHOLDER_MAPS[placeholder_url]
@@ -285,62 +272,31 @@ class Test(datasets.GeneratorBasedBuilder):
                 for target in targets
             )
         )
-        # tmp_paths = dl_manager.download(
-        #          dict(   (
-        #                 placeholder_key,
-        #                 dict(
-        #                     (target, _URLS[target][placeholder_key])
-        #                     for target in targets
-        #                 ),
-        #             )
-        #             for placeholder_key in ("dev",)
-        #         )
-        #                                  )
-        # raise Exception("HELLO BEFORE")   
-        # mapped_paths = {"dev":{}}
-        # for key,value in tmp_paths["dev"].items():
-        #     with open(value[0], "wb") as out:
-        #         mapped_paths['dev'][key] = (value[0])
-        #         for tmp_path in value[1:]:
-        #             with open(tmp_path, "rb") as tmp:
-        #                 copyfileobj(tmp, out)
-        #             #tmp_path.unlink()
-        # raise Exception("HELLO")            
-        mapped_paths =  dl_manager.download_and_extract(
-                 dict( (
+
+        mapped_paths = dl_manager.extract(
+            dl_manager.download_custom(
+                dict(
+                    (
                         placeholder_key,
                         dict(
                             (target, _URLS[target][placeholder_key])
                             for target in targets
                         ),
-                 )
-                    for placeholder_key in ("test",)
-                )
-                                         )
+                    )
+                    for placeholder_key in ("placeholder", "test")
+                ),
+                download_custom,
+            )
+        )
 
-        #raise Exception(mapped_paths)
-        
-        # tmp_paths = dl_manager.extract_and_download(
-            
-        #         dict(
-        #             (
-        #                 placeholder_key,
-        #                 dict(
-        #                     (target, _URLS[target][placeholder_key])
-        #                     for target in targets
-        #                 ),
-        #             )
-        #             for placeholder_key in ("placeholder")
-        #         ))
-        # with open(tmp_paths[0], "wb") as out:
-        #     for tmp_path in tmp_paths[1:]:
-        #         with open(tmp_path, "rb") as tmp:
-        #             copyfileobj(tmp, out)
-        #         tmp_path.unlink()
-        # mapped_paths = mapped_paths.append(tmp_paths[0])
-        # print(mapped_paths)
-                
         return [
+            datasets.SplitGenerator(
+                name="train",
+                gen_kwargs={
+                    "paths": mapped_paths["placeholder"],
+                    "meta_paths": metadata,
+                },
+            ),
             datasets.SplitGenerator(
                 name="test",
                 gen_kwargs={
@@ -348,13 +304,6 @@ class Test(datasets.GeneratorBasedBuilder):
                     "meta_paths": metadata,
                 },
             ),
-            # datasets.SplitGenerator(
-            #     name="dev",
-            #     gen_kwargs={
-            #         "paths": mapped_paths["dev"],
-            #         "meta_paths": metadata,
-            #     },
-            # ),
         ]
 
     def _generate_examples(self, paths, meta_paths):