{
 "<h1>Train a small model on CIFAR 10</h1>\n<p>This trains a small model on CIFAR 10 to test how much <a href=\"index.html\">distillation</a> benefits.</p>\n": "<h1>CIFAR 10 \u3067\u5c0f\u578b\u30e2\u30c7\u30eb\u3092\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3057\u3088\u3046</h1>\n<p>\u3053\u308c\u306b\u3088\u308a\u3001CIFAR 10\u306e\u5c0f\u578b\u30e2\u30c7\u30eb\u3092\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3057\u3066\u3001<a href=\"index.html\">\u84b8\u7559\u306b\u3069\u308c\u3060\u3051\u306e\u30e1\u30ea\u30c3\u30c8\u304c\u3042\u308b\u304b\u3092\u30c6\u30b9\u30c8\u3057\u307e\u3059</a>\u3002</p>\n",
 "<h2>Configurations</h2>\n<p>We use <a href=\"../experiments/cifar10.html\"><span translate=no>_^_0_^_</span></a> which defines all the dataset related configurations, optimizer, and a training loop.</p>\n": "<h2>\u30b3\u30f3\u30d5\u30a3\u30ae\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3</h2>\n<p>\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u95a2\u9023\u3059\u308b\u3059\u3079\u3066\u306e\u69cb\u6210\u3001\u30aa\u30d7\u30c6\u30a3\u30de\u30a4\u30b6\u30fc\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30eb\u30fc\u30d7\u3092\u5b9a\u7fa9\u3059\u308b\u3082\u306e\u3092\u4f7f\u7528\u3057\u3066\u3044\u307e\u3059<a href=\"../experiments/cifar10.html\"><span translate=no>_^_0_^_</span></a>\u3002</p>\n",
 "<h3>Create model</h3>\n": "<h3>\u30e2\u30c7\u30eb\u4f5c\u6210</h3>\n",
 "<h3>VGG style model for CIFAR-10 classification</h3>\n<p>This derives from the <a href=\"../experiments/cifar10.html\">generic VGG style architecture</a>.</p>\n": "<h3>CIFAR-10 \u5206\u985e\u7528\u306e VGG \u30b9\u30bf\u30a4\u30eb\u30e2\u30c7\u30eb</h3>\n<p><a href=\"../experiments/cifar10.html\">\u3053\u308c\u306f\u4e00\u822c\u7684\u306a VGG \u30b9\u30bf\u30a4\u30eb\u306e\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u306b\u7531\u6765\u3057\u307e\u3059</a>\u3002</p>\n",
 "<p> </p>\n": "<p></p>\n",
 "<p> Create a convolution layer and the activations</p>\n": "<p>\u30b3\u30f3\u30dc\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30ec\u30a4\u30e4\u30fc\u3068\u30a2\u30af\u30c6\u30a3\u30d9\u30fc\u30b7\u30e7\u30f3\u306e\u4f5c\u6210</p>\n",
 "<p>Batch normalization </p>\n": "<p>\u30d0\u30c3\u30c1\u6b63\u898f\u5316</p>\n",
 "<p>Convolution layer </p>\n": "<p>\u30b3\u30f3\u30dc\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30ec\u30a4\u30e4\u30fc</p>\n",
 "<p>Create a model with given convolution sizes (channels) </p>\n": "<p>\u4e0e\u3048\u3089\u308c\u305f\u7573\u307f\u8fbc\u307f\u30b5\u30a4\u30ba (\u30c1\u30e3\u30cd\u30eb) \u3067\u30e2\u30c7\u30eb\u3092\u4f5c\u6210</p>\n",
 "<p>Create configurations </p>\n": "<p>\u69cb\u6210\u306e\u4f5c\u6210</p>\n",
 "<p>Create experiment </p>\n": "<p>\u5b9f\u9a13\u3092\u4f5c\u6210</p>\n",
 "<p>Load configurations </p>\n": "<p>\u69cb\u6210\u3092\u30ed\u30fc\u30c9</p>\n",
 "<p>Print number of parameters in the model </p>\n": "<p>\u30e2\u30c7\u30eb\u5185\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u6570\u3092\u51fa\u529b\u3057\u307e\u3059</p>\n",
 "<p>ReLU activation </p>\n": "<p>ReLU \u30a2\u30af\u30c6\u30a3\u30d9\u30fc\u30b7\u30e7\u30f3</p>\n",
 "<p>Set model for saving/loading </p>\n": "<p>\u4fdd\u5b58/\u8aad\u307f\u8fbc\u307f\u7528\u306e\u30e2\u30c7\u30eb\u3092\u8a2d\u5b9a</p>\n",
 "<p>Start the experiment and run the training loop </p>\n": "<p>\u5b9f\u9a13\u3092\u958b\u59cb\u3057\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30eb\u30fc\u30d7\u3092\u5b9f\u884c\u3057\u307e\u3059</p>\n",
 "Train a small model on CIFAR 10": "CIFAR 10 \u3067\u5c0f\u578b\u30e2\u30c7\u30eb\u3092\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3057\u3088\u3046",
 "Train a small model on CIFAR 10 to test how much distillation benefits.": "CIFAR 10\u3067\u5c0f\u578b\u30e2\u30c7\u30eb\u3092\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3057\u3066\u3001\u84b8\u7559\u306b\u3069\u308c\u3060\u3051\u306e\u30e1\u30ea\u30c3\u30c8\u304c\u3042\u308b\u304b\u3092\u30c6\u30b9\u30c8\u3057\u307e\u3059\u3002"
}