{"id":27666,"date":"2024-03-17T10:04:23","date_gmt":"2024-03-17T01:04:23","guid":{"rendered":"https:\/\/www.silicloud.com\/ja\/blog\/pytorch%e3%81%aetorch-utils-data-dataloader%e3%82%92%e3%81%a9%e3%81%ae%e3%82%88%e3%81%86%e3%81%ab%e4%bd%bf%e7%94%a8%e3%81%99%e3%82%8b%e3%81%8b%ef%bc%9f\/"},"modified":"2024-03-22T16:45:26","modified_gmt":"2024-03-22T07:45:26","slug":"pytorch%e3%81%aetorch-utils-data-dataloader%e3%82%92%e3%81%a9%e3%81%ae%e3%82%88%e3%81%86%e3%81%ab%e4%bd%bf%e7%94%a8%e3%81%99%e3%82%8b%e3%81%8b%ef%bc%9f","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/ja\/blog\/pytorch%e3%81%aetorch-utils-data-dataloader%e3%82%92%e3%81%a9%e3%81%ae%e3%82%88%e3%81%86%e3%81%ab%e4%bd%bf%e7%94%a8%e3%81%99%e3%82%8b%e3%81%8b%ef%bc%9f\/","title":{"rendered":"PyTorch\u306etorch.utils.data.dataloader\u3092\u3069\u306e\u3088\u3046\u306b\u4f7f\u7528\u3059\u308b\u304b\uff1f"},"content":{"rendered":"

PyTorch\u306etorch.utils.data.DataLoader\u306f\u3001\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u8fbc\u307f\u51e6\u7406\u3059\u308b\u305f\u3081\u306e\u30c4\u30fc\u30eb\u3067\u3059\u3002\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30d0\u30c3\u30c1\u306b\u5206\u5272\u3057\u3001\u4e26\u5217\u8aad\u307f\u8fbc\u307f\u3092\u884c\u3044\u3001\u30c7\u30fc\u30bf\u306e\u30b7\u30e3\u30c3\u30d5\u30eb\u3084\u30de\u30eb\u30c1\u30b9\u30ec\u30c3\u30c9\u8aad\u307f\u8fbc\u307f\u6a5f\u80fd\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002torch.utils.data.DataLoader\u306e\u4f7f\u7528\u6cd5\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\uff1a<\/p>\n

    \n
  1. \u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3084\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/li>\n<\/ol>\n
    import<\/span> torch\r\nfrom<\/span> torch.utils.data import<\/span> DataLoader\r\nfrom<\/span> torch.utils.data.dataset import<\/span> Dataset\r\n<\/code><\/pre>\n
      \n
    1. \u30ab\u30b9\u30bf\u30e0\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u30af\u30e9\u30b9\uff08Dataset\uff09\u3092\u4f5c\u6210\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/li>\n<\/ol>\n
      class<\/span> CustomDataset<\/span>(Dataset<\/span>):\r\n    def<\/span> __init__<\/span>(self, data<\/span>):\r\n        self.data = data\r\n    \r\n    def<\/span> __getitem__<\/span>(self, index<\/span>):\r\n        # \u8fd4\u56de\u6570\u636e\u548c\u6807\u7b7e<\/span>\r\n        x = self.data[index]\r\n        y = 0<\/span>  # \u6807\u7b7e\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u60c5\u51b5\u8fdb\u884c\u4fee\u6539<\/span>\r\n        return<\/span> x, y\r\n    \r\n    def<\/span> __len__<\/span>(self<\/span>):\r\n        return<\/span> len<\/span>(self.data)\r\n<\/code><\/pre>\n
        \n
      1. \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u3092\u4f5c\u6210\u3059\u308b\uff1a<\/li>\n<\/ol>\n
        data = [...]  # \u6570\u636e\u96c6<\/span>\r\ndataset = CustomDataset(data)\r\n<\/code><\/pre>\n
          \n
        1. \u30c7\u30fc\u30bf\u30ed\u30fc\u30c0\u30fc\uff08DataLoader\uff09\u3092\u4f5c\u6210\u3059\u308b:<\/li>\n<\/ol>\n
          batch_size = 32<\/span>  # \u6bcf\u4e2a\u6279\u6b21\u7684\u6837\u672c\u6570\u91cf<\/span>\r\nshuffle = True<\/span>  # \u662f\u5426\u6253\u4e71\u6570\u636e\u96c6<\/span>\r\nnum_workers = 4<\/span>  # \u52a0\u8f7d\u6570\u636e\u7684\u7ebf\u7a0b\u6570\u91cf<\/span>\r\n\r\ndataloader = DataLoader(dataset, batch_size=batch_size, shuffle=shuffle, num_workers=num_workers)\r\n<\/code><\/pre>\n
            \n
          1. \u30c7\u30fc\u30bf\u30ed\u30fc\u30c0\u30fc\u3092\u53cd\u5fa9\u51e6\u7406\u3057\u3066\u30c7\u30fc\u30bf\u306b\u30a2\u30af\u30bb\u30b9\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n
            for<\/span> batch_data, batch_labels in<\/span> dataloader:\r\n    # \u5bf9\u6279\u6b21\u6570\u636e\u8fdb\u884c\u5904\u7406<\/span>\r\n    print<\/span>(batch_data.shape)\r\n    print<\/span>(batch_labels.shape)\r\n<\/code><\/pre>\n
            \u4e0a\u8a18\u306e\u30b3\u30fc\u30c9\u3067\u306f\u3001\u307e\u305a\u3001\u30ab\u30b9\u30bf\u30e0\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u30af\u30e9\u30b9\uff08CustomDataset\uff09\u3092\u5b9a\u7fa9\u3057\u3001\u6b21\u306b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\uff08dataset\uff09\u3092\u4f5c\u6210\u3057\u3066\u3001\u305d\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf\u30ed\u30fc\u30c0\u30fc\uff08dataloader\uff09\u3092\u4f5c\u6210\u3057\u307e\u3057\u305f\u3002\u30c7\u30fc\u30bf\u30ed\u30fc\u30c0\u30fc\u3092\u30a4\u30c6\u30ec\u30fc\u30c8\u3059\u308b\u3068\u3001\u5404\u30d0\u30c3\u30c1\u306e\u30c7\u30fc\u30bf\u3068\u30e9\u30d9\u30eb\u3092\u53d6\u5f97\u3057\u3066\u51e6\u7406\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
            PyTorch\u306etorch.utils.data.DataLoader\u306f\u3001\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u8fbc\u307f\u51e6\u7406\u3059\u308b\u305f\u3081\u306e\u30c4\u30fc\u30eb\u3067\u3059\u3002\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30d0\u30c3\u30c1\u306b\u5206\u5272\u3057\u3001\u4e26\u5217\u8aad\u307f\u8fbc\u307f\u3092\u884c\u3044\u3001\u30c7\u30fc\u30bf\u306e\u30b7\u30e3\u30c3\u30d5\u30eb\u3084\u30de\u30eb\u30c1\u30b9\u30ec\u30c3\u30c9\u8aad\u307f\u8fbc\u307f\u6a5f\u80fd\u3092\u63d0\u4f9b\u3057 […]<\/p>\n","protected":false},"author":7,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-27666","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\nPyTorch\u306etorch.utils.data.dataloader\u3092\u3069\u306e\u3088\u3046\u306b\u4f7f\u7528\u3059\u308b\u304b\uff1f - Blog - Silicon Cloud<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.silicloud.com\/ja\/blog\/pytorch\u306etorch-utils-data-dataloader\u3092\u3069\u306e\u3088\u3046\u306b\u4f7f\u7528\u3059\u308b\u304b\uff1f\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PyTorch\u306etorch.utils.data.dataloader\u3092\u3069\u306e\u3088\u3046\u306b\u4f7f\u7528\u3059\u308b\u304b\uff1f\" \/>\n<meta property=\"og:description\" content=\"PyTorch\u306etorch.utils.data.DataLoader\u306f\u3001\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u8fbc\u307f\u51e6\u7406\u3059\u308b\u305f\u3081\u306e\u30c4\u30fc\u30eb\u3067\u3059\u3002\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30d0\u30c3\u30c1\u306b\u5206\u5272\u3057\u3001\u4e26\u5217\u8aad\u307f\u8fbc\u307f\u3092\u884c\u3044\u3001\u30c7\u30fc\u30bf\u306e\u30b7\u30e3\u30c3\u30d5\u30eb\u3084\u30de\u30eb\u30c1\u30b9\u30ec\u30c3\u30c9\u8aad\u307f\u8fbc\u307f\u6a5f\u80fd\u3092\u63d0\u4f9b\u3057 […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.silicloud.com\/ja\/blog\/pytorch\u306etorch-utils-data-dataloader\u3092\u3069\u306e\u3088\u3046\u306b\u4f7f\u7528\u3059\u308b\u304b\uff1f\/\" \/>\n<meta property=\"og:site_name\" content=\"Blog - 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