{"author_url":"https://blog.hatena.ne.jp/derwind/","version":"1.0","published":"2021-11-18 01:01:11","provider_url":"https://hatena.blog","author_name":"derwind","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/d/derwind/20211118/20211118010032.png","blog_url":"https://randommemory.hatenablog.com/","width":"100%","height":"190","description":"ch06 \u306e Rnnlm \u3092 DeZero \u306b\u30dd\u30fc\u30c6\u30a3\u30f3\u30b0\u3059\u308b\u3002\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u611f\u3058\u3067\u826f\u3044\u306f\u305a\u30fb\u30fb\u30fb class Rnnlm(Model): def __init__(self, vocab_size, wordvec_size, hidden_size): super().__init__() V, D, H = vocab_size, wordvec_size, hidden_size self.embedding = L.EmbedID(V, D) self.embedding.W.data /= 100 self.lstm = L.LSTM(H, D) for gate in ['x2f'\u2026","categories":["machine_learning"],"title":"\u30bc\u30ed\u3064\u304f 2 (17)","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Frandommemory.hatenablog.com%2Fentry%2F2021%2F11%2F18%2F010111\" title=\"\u30bc\u30ed\u3064\u304f 2 (17) - \u3089\u3093\u3060\u3080\u306a\u8a18\u61b6\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","provider_name":"Hatena Blog","blog_title":"\u3089\u3093\u3060\u3080\u306a\u8a18\u61b6","type":"rich","url":"https://randommemory.hatenablog.com/entry/2021/11/18/010111"}