From 02867b96ae5876cc0b6790c59de962eb41600ae7 Mon Sep 17 00:00:00 2001
From: Mokhov Andrey <asmokhov@mail.ru>
Date: Mon, 17 Apr 2023 16:36:30 +0300
Subject: [PATCH] lab04: reset model

---
 labs/OATD_LR4_metod.ipynb | 32 ++++++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)

diff --git a/labs/OATD_LR4_metod.ipynb b/labs/OATD_LR4_metod.ipynb
index 8b02b49..d7d453e 100644
--- a/labs/OATD_LR4_metod.ipynb
+++ b/labs/OATD_LR4_metod.ipynb
@@ -1367,6 +1367,38 @@
     "### Обучение!"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Обратим внимание, что перед очередным обучением нужно сбросить веса модели. Проще всего это сделать, заново объявив и скомпилировав модель:\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'MyModel' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[1], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mMyModel\u001b[49m(\n\u001b[0;32m      2\u001b[0m     vocab_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mlen\u001b[39m(ids_from_chars\u001b[38;5;241m.\u001b[39mget_vocabulary()),\n\u001b[0;32m      3\u001b[0m     embedding_dim\u001b[38;5;241m=\u001b[39membedding_dim,\n\u001b[0;32m      4\u001b[0m     rnn_units\u001b[38;5;241m=\u001b[39mrnn_units)\n\u001b[0;32m      5\u001b[0m model\u001b[38;5;241m.\u001b[39mcompile(optimizer\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124madam\u001b[39m\u001b[38;5;124m'\u001b[39m, loss\u001b[38;5;241m=\u001b[39mloss)\n",
+      "\u001b[1;31mNameError\u001b[0m: name 'MyModel' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "model = MyModel(\n",
+    "    vocab_size=len(ids_from_chars.get_vocabulary()),\n",
+    "    embedding_dim=embedding_dim,\n",
+    "    rnn_units=rnn_units)\n",
+    "model.compile(optimizer='adam', loss=loss)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 36,