7.2.2 TensorFlow的可视化框架.ipynb

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     "name": "stderr",
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     "text": [
      "Using TensorFlow backend.\n"
     ]
    },
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     "name": "stdout",
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     "text": [
      "WARNING:tensorflow:From /home/fc/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "embed (Embedding)            (None, 500, 128)          256000    \n",
      "_________________________________________________________________\n",
      "conv1d_1 (Conv1D)            (None, 494, 32)           28704     \n",
      "_________________________________________________________________\n",
      "max_pooling1d_1 (MaxPooling1 (None, 98, 32)            0         \n",
      "_________________________________________________________________\n",
      "conv1d_2 (Conv1D)            (None, 92, 32)            7200      \n",
      "_________________________________________________________________\n",
      "global_max_pooling1d_1 (Glob (None, 32)                0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 1)                 33        \n",
      "=================================================================\n",
      "Total params: 291,937\n",
      "Trainable params: 291,937\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "# 使用了 TensorBoard 的文本分类模型\n",
    "import keras\n",
    "from keras import layers\n",
    "from keras.datasets import imdb\n",
    "from keras.preprocessing import sequence\n",
    "max_features = 2000\n",
    "max_len = 500\n",
    "(x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=max_features)\n",
    "x_train = sequence.pad_sequences(x_train, maxlen=max_len)\n",
    "x_test = sequence.pad_sequences(x_test, maxlen=max_len)\n",
    "\n",
    "model = keras.models.Sequential()\n",
    "model.add(layers.Embedding(max_features, 128,\n",
    "                           input_length=max_len,\n",
    "                        name='embed'))\n",
    "model.add(layers.Conv1D(32, 7, activation='relu'))\n",
    "model.add(layers.MaxPooling1D(5))\n",
    "model.add(layers.Conv1D(32, 7, activation='relu'))\n",
    "model.add(layers.GlobalMaxPooling1D())\n",
    "model.add(layers.Dense(1))\n",
    "model.summary()\n",
    "model.compile(optimizer='rmsprop',\n",
    "              loss='binary_crossentropy',\n",
    "              metrics=['acc'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ! mkdir my_log_dir "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用一个 TensorBoard 回调函数来训练模型\n",
    "callbacks = [\n",
    " keras.callbacks.TensorBoard(\n",
    " log_dir='my_log_dir',\n",
    " histogram_freq=1,\n",
    " embeddings_freq=1,\n",
    " )\n",
    "]\n",
    "history = model.fit(x_train, y_train,\n",
    " epochs=20,\n",
    " batch_size=128,\n",
    " validation_split=0.2,\n",
    " callbacks=callbacks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!tensorboard --logdir=my_log_dir"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "用浏览器打开 http://localhost:6006"
   ]
  }
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