{"provider_url":"https://hatena.blog","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fml-rand-note.hatenablog.com%2Fentry%2Ferror-keras-input_shape_argument\" title=\"Do not pass an `input_shape`/`input_dim` argument~\u306e\u89e3\u6c7a\u7b56 - \u30e9\u30f3\u30c9ML\" 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","author_name":"round-rand","type":"rich","height":"190","url":"https://ml-rand-note.hatenablog.com/entry/error-keras-input_shape_argument","version":"1.0","blog_title":"\u30e9\u30f3\u30c9ML","image_url":null,"description":"\u8b66\u544a\u306e\u767a\u751f\u72b6\u6cc1 keras\u3092\u4f7f\u3063\u3066\u3001 model = keras.Sequential([ keras.layers.Dense(16, activation = 'relu', input_shape=[4]), # \u4ee5\u4e0b\u7701\u7565 ]) \u3068\u3044\u3046\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u305f\u3068\u3053\u308d\u3001 UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in t\u2026","width":"100%","categories":["\u30a8\u30e9\u30fc\u89e3\u6c7a","keras"],"title":"Do not pass an `input_shape`/`input_dim` argument~\u306e\u89e3\u6c7a\u7b56","blog_url":"https://ml-rand-note.hatenablog.com/","author_url":"https://blog.hatena.ne.jp/round-rand/","published":"2025-02-17 00:00:00"}