mnist.ja.json

{
 "<h1>MNIST Experiment</h1>\n": "<h1>MNIST \u5b9f\u9a13</h1>\n",
 "<h3>Default optimizer configurations</h3>\n": "<h3>\u30c7\u30d5\u30a9\u30eb\u30c8\u306e\u30aa\u30d7\u30c6\u30a3\u30de\u30a4\u30b6\u30fc\u69cb\u6210</h3>\n",
 "<h3>Initialization</h3>\n": "<h3>\u521d\u671f\u5316</h3>\n",
 "<h3>Training or validation step</h3>\n": "<h3>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u307e\u305f\u306f\u691c\u8a3c\u30b9\u30c6\u30c3\u30d7</h3>\n",
 "<p> <a id=\"MNISTConfigs\"></a></p>\n<h2>Trainer configurations</h2>\n": "<p><a id=\"MNISTConfigs\"></a></p>\n<h2>\u30c8\u30ec\u30fc\u30ca\u30fc\u69cb\u6210</h2>\n",
 "<p>Accuracy function </p>\n": "<p>\u7cbe\u5ea6\u6a5f\u80fd</p>\n",
 "<p>Add a hook to log module outputs </p>\n": "<p>\u30e2\u30b8\u30e5\u30fc\u30eb\u51fa\u529b\u3092\u30ed\u30b0\u306b\u8a18\u9332\u3059\u308b\u30d5\u30c3\u30af\u3092\u8ffd\u52a0</p>\n",
 "<p>Add accuracy as a state module. The name is probably confusing, since it&#x27;s meant to store states between training and validation for RNNs. This will keep the accuracy metric stats separate for training and validation. </p>\n": "<p>\u30b9\u30c6\u30fc\u30c8\u30e2\u30b8\u30e5\u30fc\u30eb\u3068\u3057\u3066\u7cbe\u5ea6\u3092\u8ffd\u52a0\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u3053\u306e\u540d\u524d\u306f\u3001RNN \u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3068\u691c\u8a3c\u306e\u9593\u306e\u72b6\u614b\u3092\u4fdd\u5b58\u3059\u308b\u305f\u3081\u306e\u3082\u306e\u306a\u306e\u3067\u3001\u304a\u305d\u3089\u304f\u308f\u304b\u308a\u306b\u304f\u3044\u3067\u3057\u3087\u3046\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u7cbe\u5ea6\u6307\u6a19\u306e\u7d71\u8a08\u60c5\u5831\u304c\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u7528\u3068\u691c\u8a3c\u7528\u306b\u5225\u3005\u306b\u4fdd\u6301\u3055\u308c\u307e\u3059\u3002</p>\n",
 "<p>Calculate and log accuracy </p>\n": "<p>\u7cbe\u5ea6\u306e\u8a08\u7b97\u3068\u8a18\u9332</p>\n",
 "<p>Calculate and log loss </p>\n": "<p>\u640d\u5931\u306e\u8a08\u7b97\u3068\u8a18\u9332</p>\n",
 "<p>Calculate gradients </p>\n": "<p>\u52fe\u914d\u306e\u8a08\u7b97</p>\n",
 "<p>Classification model </p>\n": "<p>\u5206\u985e\u30e2\u30c7\u30eb</p>\n",
 "<p>Clear the gradients </p>\n": "<p>\u30b0\u30e9\u30c7\u30fc\u30b7\u30e7\u30f3\u3092\u30af\u30ea\u30a2</p>\n",
 "<p>Get model outputs. </p>\n": "<p>\u30e2\u30c7\u30eb\u51fa\u529b\u3092\u53d6\u5f97\u3057\u307e\u3059\u3002</p>\n",
 "<p>Log the model parameters and gradients on last batch of every epoch </p>\n": "<p>\u5404\u30a8\u30dd\u30c3\u30af\u306e\u6700\u5f8c\u306e\u30d0\u30c3\u30c1\u3067\u30e2\u30c7\u30eb\u30d1\u30e9\u30e1\u30fc\u30bf\u3068\u52fe\u914d\u3092\u8a18\u9332\u3057\u307e\u3059</p>\n",
 "<p>Loss function </p>\n": "<p>\u640d\u5931\u95a2\u6570</p>\n",
 "<p>Move data to the device </p>\n": "<p>\u30c7\u30fc\u30bf\u3092\u30c7\u30d0\u30a4\u30b9\u306b\u79fb\u52d5</p>\n",
 "<p>Number of epochs to train for </p>\n": "<p>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u5bfe\u8c61\u30a8\u30dd\u30c3\u30af\u306e\u6570</p>\n",
 "<p>Number of times to switch between training and validation within an epoch </p>\n": "<p>1 \u3064\u306e\u30a8\u30dd\u30c3\u30af\u5185\u3067\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3068\u691c\u8a3c\u3092\u5207\u308a\u66ff\u3048\u308b\u56de\u6570</p>\n",
 "<p>Optimizer </p>\n": "<p>\u30aa\u30d7\u30c6\u30a3\u30de\u30a4\u30b6\u30fc</p>\n",
 "<p>Save the tracked metrics </p>\n": "<p>\u8ffd\u8de1\u3057\u305f\u30e1\u30c8\u30ea\u30af\u30b9\u3092\u4fdd\u5b58\u3059\u308b</p>\n",
 "<p>Set tracker configurations </p>\n": "<p>\u30c8\u30e9\u30c3\u30ab\u30fc\u69cb\u6210\u3092\u8a2d\u5b9a</p>\n",
 "<p>Take optimizer step </p>\n": "<p>\u6700\u9069\u5316\u306e\u4e00\u6b69\u3092\u8e0f\u307f\u51fa\u3059</p>\n",
 "<p>Train the model </p>\n": "<p>\u30e2\u30c7\u30eb\u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0</p>\n",
 "<p>Training device </p>\n": "<p>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30c7\u30d0\u30a4\u30b9</p>\n",
 "<p>Training/Evaluation mode </p>\n": "<p>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0/\u8a55\u4fa1\u30e2\u30fc\u30c9</p>\n",
 "<p>Update global step (number of samples processed) when in training mode </p>\n": "<p>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30e2\u30fc\u30c9\u6642\u306b\u30b0\u30ed\u30fc\u30d0\u30eb\u30b9\u30c6\u30c3\u30d7 (\u51e6\u7406\u3055\u308c\u305f\u30b5\u30f3\u30d7\u30eb\u6570) \u3092\u66f4\u65b0</p>\n",
 "<p>Whether to capture model outputs </p>\n": "<p>\u30e2\u30c7\u30eb\u51fa\u529b\u3092\u30ad\u30e3\u30d7\u30c1\u30e3\u3059\u308b\u304b\u3069\u3046\u304b</p>\n",
 "MNIST Experiment": "MNIST \u5b9f\u9a13",
 "This is a reusable trainer for MNIST dataset": "\u3053\u308c\u306fMNIST\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u518d\u5229\u7528\u53ef\u80fd\u306a\u30c8\u30ec\u30fc\u30ca\u30fc\u3067\u3059"
}