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{
"<h1>Transformer Auto-Regression Experiment</h1>\n<p><a href=\"https://colab.research.google.com/github/labmlai/annotated_deep_learning_paper_implementations/blob/master/labml_nn/transformers/basic/autoregressive_experiment.ipynb\"><span translate=no>_^_0_^_</span></a></p>\n<p>This trains a simple transformer introduced in <a href=\"https://papers.labml.ai/paper/1706.03762\">Attention Is All You Need</a> on an NLP auto-regression task (with Tiny Shakespeare dataset).</p>\n": "<h1>\u30c8\u30e9\u30f3\u30b9\u30d5\u30a9\u30fc\u30de\u30fc\u81ea\u52d5\u56de\u5e30\u5b9f\u9a13</h1>\n<p><a href=\"https://colab.research.google.com/github/labmlai/annotated_deep_learning_paper_implementations/blob/master/labml_nn/transformers/basic/autoregressive_experiment.ipynb\"><span translate=no>_^_0_^_</span></a></p>\n<p>\u3053\u308c\u306f\u3001\u300c<a href=\"https://papers.labml.ai/paper/1706.03762\">\u5fc5\u8981\u306a\u306e\u306f\u6ce8\u610f\u3060\u3051</a>\u300d\u3067\u7d39\u4ecb\u3057\u305f\u30b7\u30f3\u30d7\u30eb\u306a\u30c8\u30e9\u30f3\u30b9\u30d5\u30a9\u30fc\u30de\u30fc\u3092NLP\u81ea\u52d5\u56de\u5e30\u30bf\u30b9\u30af\uff08Tiny Shakespeare\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f7f\u7528\uff09\u3067\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3057\u307e\u3059\u3002</p>\n",
"<h2>Auto-Regressive model</h2>\n": "<h2>\u81ea\u5df1\u56de\u5e30\u30e2\u30c7\u30eb</h2>\n",
"<h2>Configurations</h2>\n<p>This inherits from <a href=\"../../experiments/nlp_autoregression.html#NLPAutoRegressionConfigs\"><span translate=no>_^_0_^_</span></a></p>\n": "<h2>\u30b3\u30f3\u30d5\u30a3\u30ae\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3</h2>\n<p>\u3053\u308c\u306f\u4ee5\u4e0b\u304b\u3089\u7d99\u627f\u3055\u308c\u307e\u3059 <a href=\"../../experiments/nlp_autoregression.html#NLPAutoRegressionConfigs\"><span translate=no>_^_0_^_</span></a></p>\n",
"<h3>Transformer configurations</h3>\n": "<h3>\u5909\u5727\u5668\u69cb\u6210</h3>\n",
"<p> </p>\n": "<p></p>\n",
"<p> Create GPT model and initialize weights</p>\n": "<p>GPT \u30e2\u30c7\u30eb\u306e\u4f5c\u6210\u3068\u91cd\u307f\u306e\u521d\u671f\u5316</p>\n",
"<p>Batch size <span translate=no>_^_0_^_</span> </p>\n": "<p>\u30d0\u30c3\u30c1\u30b5\u30a4\u30ba <span translate=no>_^_0_^_</span></p>\n",
"<p>Create configs </p>\n": "<p>\u30b3\u30f3\u30d5\u30a3\u30b0\u306e\u4f5c\u6210</p>\n",
"<p>Create experiment </p>\n": "<p>\u5b9f\u9a13\u3092\u4f5c\u6210</p>\n",
"<p>Create subsequent mask if mask is not initialized or if the size of the mask is different </p>\n": "<p>\u30de\u30b9\u30af\u304c\u521d\u671f\u5316\u3055\u308c\u3066\u3044\u306a\u3044\u5834\u5408\u3084\u30de\u30b9\u30af\u306e\u30b5\u30a4\u30ba\u304c\u7570\u306a\u308b\u5834\u5408\u306f\u3001\u5f8c\u7d9a\u306e\u30de\u30b9\u30af\u3092\u4f5c\u6210\u3057\u307e\u3059</p>\n",
"<p>GPT model </p>\n": "<p>GPT \u30e2\u30c7\u30eb</p>\n",
"<p>Get logits </p>\n": "<p>\u30ed\u30b8\u30c3\u30c8\u3092\u53d6\u5f97</p>\n",
"<p>Get the token embeddings with positional encodings </p>\n": "<p>\u4f4d\u7f6e\u30a8\u30f3\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u306b\u3088\u308b\u30c8\u30fc\u30af\u30f3\u306e\u57cb\u3081\u8fbc\u307f\u3092\u53d6\u5f97</p>\n",
"<p>Model size </p>\n": "<p>\u30e2\u30c7\u30eb\u30b5\u30a4\u30ba</p>\n",
"<p>Override configurations </p>\n": "<p>\u30aa\u30fc\u30d0\u30fc\u30e9\u30a4\u30c9\u8a2d\u5b9a</p>\n",
"<p>Prompt separator is blank </p>\n": "<p>\u30d7\u30ed\u30f3\u30d7\u30c8\u30bb\u30d1\u30ec\u30fc\u30bf\u304c\u7a7a\u767d</p>\n",
"<p>Return results (second value is for state, since our trainer is used with RNNs also) </p>\n": "<p>\u7d50\u679c\u3092\u8fd4\u3057\u307e\u3059\uff08\u30c8\u30ec\u30fc\u30ca\u30fc\u306fRNN\u3067\u3082\u4f7f\u7528\u3055\u308c\u308b\u305f\u3081\u30012\u756a\u76ee\u306e\u5024\u306f\u72b6\u614b\u7528\u3067\u3059\uff09</p>\n",
"<p>Run training </p>\n": "<p>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3092\u5b9f\u884c</p>\n",
"<p>Set models for saving and loading </p>\n": "<p>\u4fdd\u5b58\u304a\u3088\u3073\u8aad\u307f\u8fbc\u307f\u7528\u306e\u30e2\u30c7\u30eb\u3092\u8a2d\u5b9a\u3059\u308b</p>\n",
"<p>Set the vocabulary sizes for embeddings and generating logits </p>\n": "<p>\u57cb\u3081\u8fbc\u307f\u3084\u30ed\u30b8\u30c3\u30c8\u306e\u751f\u6210\u306b\u4f7f\u7528\u3059\u308b\u30dc\u30ad\u30e3\u30d6\u30e9\u30ea\u30fc\u30b5\u30a4\u30ba\u3092\u8a2d\u5b9a</p>\n",
"<p>Start the experiment </p>\n": "<p>\u5b9f\u9a13\u3092\u59cb\u3081\u308b</p>\n",
"<p>Starting prompt for sampling </p>\n": "<p>\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u306e\u958b\u59cb\u30d7\u30ed\u30f3\u30d7\u30c8</p>\n",
"<p>Subsequent mask, will mask out tokens from seeing future tokens </p>\n": "<p>\u6b21\u306b\u30de\u30b9\u30af\u3059\u308b\u3068\u3001\u30c8\u30fc\u30af\u30f3\u304c\u30de\u30b9\u30af\u3055\u308c\u3001\u5c06\u6765\u306e\u30c8\u30fc\u30af\u30f3\u304c\u898b\u3048\u306a\u304f\u306a\u308a\u307e\u3059</p>\n",
"<p>Switch between training and validation for <span translate=no>_^_0_^_</span> times per epoch </p>\n": "<p>\u30a8\u30dd\u30c3\u30af\u3054\u3068\u306b\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3068\u691c\u8a3c\u3092\u5207\u308a\u66ff\u3048\u308b <span translate=no>_^_0_^_</span></p>\n",
"<p>The mask will be initialized on the first call </p>\n": "<p>\u30de\u30b9\u30af\u306f\u6700\u521d\u306e\u547c\u3073\u51fa\u3057\u3067\u521d\u671f\u5316\u3055\u308c\u307e\u3059</p>\n",
"<p>Train for 32 epochs </p>\n": "<p>32 \u30a8\u30dd\u30c3\u30af\u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0</p>\n",
"<p>Transformer </p>\n": "<p>\u5909\u5727\u5668</p>\n",
"<p>Transformer encoder </p>\n": "<p>\u30c8\u30e9\u30f3\u30b9\u30a8\u30f3\u30b3\u30fc\u30c0\u30fc</p>\n",
"<p>Use <a href=\"../../optimizers/noam.html\">Noam optimizer</a> </p>\n": "<p><a href=\"../../optimizers/noam.html\">Noam</a> \u30aa\u30d7\u30c6\u30a3\u30de\u30a4\u30b6\u3092\u4f7f\u3046</p>\n",
"<p>Use Tiny Shakespeare dataset </p>\n": "<p>\u30bf\u30a4\u30cb\u30fc\u30fb\u30b7\u30a7\u30a4\u30af\u30b9\u30d4\u30a2\u30fb\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f7f\u3046</p>\n",
"<p>Use a context size of <span translate=no>_^_0_^_</span> </p>\n": "<p>\u30b3\u30f3\u30c6\u30ad\u30b9\u30c8\u30b5\u30a4\u30ba\u3092\u6b21\u306e\u5024\u306b\u3057\u3066\u304f\u3060\u3055\u3044 <span translate=no>_^_0_^_</span></p>\n",
"<p>Use character level tokenizer </p>\n": "<p>\u30ad\u30e3\u30e9\u30af\u30bf\u30fc\u30ec\u30d9\u30eb\u306e\u30c8\u30fc\u30af\u30ca\u30a4\u30b6\u30fc\u3092\u4f7f\u3046</p>\n",
"<p>We use our <a href=\"../configs.html#TransformerConfigs\">configurable transformer implementation</a> </p>\n": "<p><a href=\"../configs.html#TransformerConfigs\">\u8a2d\u5b9a\u53ef\u80fd\u306a\u30c8\u30e9\u30f3\u30b9\u5b9f\u88c5\u3092\u4f7f\u7528\u3057\u3066\u3044\u307e\u3059</a></p>\n",
"<ul><li><span translate=no>_^_0_^_</span> is the transformer <a href=\"../models.html#Encoder\">Encoder</a> </li>\n<li><span translate=no>_^_1_^_</span> is the token <a href=\"../models.html#EmbeddingsWithLearnedPositionalEncoding\">embedding module (with positional encodings)</a> </li>\n<li><span translate=no>_^_2_^_</span> is the <a href=\"../models.html#Generator\">final fully connected layer</a> that gives the logits.</li></ul>\n": "<ul><li><span translate=no>_^_0_^_</span><a href=\"../models.html#Encoder\">\u5909\u5727\u5668\u30a8\u30f3\u30b3\u30fc\u30c0\u3067\u3059</a></li>\n<li><span translate=no>_^_1_^_</span><a href=\"../models.html#EmbeddingsWithLearnedPositionalEncoding\">\u306f\u30c8\u30fc\u30af\u30f3\u57cb\u3081\u8fbc\u307f\u30e2\u30b8\u30e5\u30fc\u30eb\u3067\u3059 (\u4f4d\u7f6e\u30a8\u30f3\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u4ed8\u304d)</a></li>\n</ul><li><span translate=no>_^_2_^_</span><a href=\"../models.html#Generator\">\u30ed\u30b8\u30c3\u30c8\u3092\u751f\u6210\u3059\u308b\u6700\u5f8c\u306e\u5b8c\u5168\u63a5\u7d9a\u5c64\u3067\u3059</a>\u3002</li>\n",
"This trains a simple transformer model on NLP auto-regression.": "\u3053\u308c\u306b\u3088\u308a\u3001\u5358\u7d14\u306a\u30c8\u30e9\u30f3\u30b9\u30d5\u30a9\u30fc\u30de\u30fc\u30e2\u30c7\u30eb\u306b NLP \u81ea\u52d5\u56de\u5e30\u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3092\u884c\u3044\u307e\u3059\u3002",
"Transformer Auto-Regression Experiment": "\u30c8\u30e9\u30f3\u30b9\u30d5\u30a9\u30fc\u30de\u30fc\u81ea\u52d5\u56de\u5e30\u5b9f\u9a13"
}