trainer.ja.json

{
 "<h3>Get trainable parameters</h3>\n<ul><li><span translate=no>_^_0_^_</span>  is the model to train </li>\n<p><em>Returns</em>  a list of parameters for training</p></ul>\n": "<h3>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u53ef\u80fd\u306a\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u53d6\u5f97</h3>\n<ul><li><span translate=no>_^_0_^_</span>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3059\u308b\u30e2\u30c7\u30eb\u3067\u3059</li>\n<p><em>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u7528\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u30ea\u30b9\u30c8\u3092\u8fd4\u3057\u307e\u3059</em></p></ul>\n",
 "<p> </p>\n": "<p></p>\n",
 "<p>Backward pass </p>\n": "<p>\u30d0\u30c3\u30af\u30ef\u30fc\u30c9\u30d1\u30b9</p>\n",
 "<p>Calculate accuracy </p>\n": "<p>\u7cbe\u5ea6\u3092\u8a08\u7b97</p>\n",
 "<p>Calculate loss </p>\n": "<p>\u640d\u5931\u306e\u8a08\u7b97</p>\n",
 "<p>Filter parameters that require gradients </p>\n": "<p>\u30b0\u30e9\u30c7\u30fc\u30b7\u30e7\u30f3\u3092\u5fc5\u8981\u3068\u3059\u308b\u30d5\u30a3\u30eb\u30bf\u30fc\u30d1\u30e9\u30e1\u30fc\u30bf\u30fc</p>\n",
 "<p>Forward pass </p>\n": "<p>\u30d5\u30a9\u30ef\u30fc\u30c9\u30d1\u30b9</p>\n",
 "<p>Get all parameters </p>\n": "<p>\u3059\u3079\u3066\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u53d6\u5f97</p>\n",
 "<p>Get predictions </p>\n": "<p>\u4e88\u6e2c\u3092\u53d6\u5f97</p>\n",
 "<p>Iterate through the batches </p>\n": "<p>\u30d0\u30c3\u30c1\u3092\u7e70\u308a\u8fd4\u3057\u51e6\u7406\u3059\u308b</p>\n",
 "<p>Move targets to the same device as output </p>\n": "<p>\u30bf\u30fc\u30b2\u30c3\u30c8\u3092\u51fa\u529b\u3068\u540c\u3058\u30c7\u30d0\u30a4\u30b9\u306b\u79fb\u52d5</p>\n",
 "<p>Optimize </p>\n": "<p>\u6700\u9069\u5316</p>\n",
 "<p>Set gradients to zero </p>\n": "<p>\u30b0\u30e9\u30c7\u30fc\u30b7\u30e7\u30f3\u3092\u30bc\u30ed\u306b\u8a2d\u5b9a</p>\n",
 "<p>Set model for train </p>\n": "<p>\u9244\u9053\u6a21\u578b\u3092\u8a2d\u5b9a</p>\n",
 "<p>tracker.add({&#x27;loss.scaled&#x27;: loss}) </p>\n": "<p>\u30c8\u30e9\u30c3\u30ab\u30fc\u8ffd\u52a0 ({'\u640d\u5931.scaled': \u640d\u5931})</p>\n",
 "<ul><li><span translate=no>_^_0_^_</span>  train/valid </li>\n<li><span translate=no>_^_1_^_</span>  is the sample </li>\n<p><em>Returns</em>  the loss, output and the target</p></ul>\n": "<ul><li><span translate=no>_^_0_^_</span>\u96fb\u8eca/\u6709\u52b9</li>\n<li><span translate=no>_^_1_^_</span>\u30b5\u30f3\u30d7\u30eb\u3067\u3059</li>\n<p>\u640d\u5931\u3001\u51fa\u529b\u3001<em>\u30bf\u30fc\u30b2\u30c3\u30c8\u3092\u8fd4\u3057\u307e\u3059</em></p></ul>\n",
 "trainer.py": "trainer.py"
}