17-vgg16-content.ipynb

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   "cell_type": "code",
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   "source": [
    "import numpy as np\n",
    "import pickle\n",
    "\n",
    "vgg16_data = np.load('vgg16/vgg16.npy', allow_pickle=True, encoding='latin1')\n",
    "print(type(vgg16_data))\n",
    "print(vgg16_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dict = vgg16_data.item()\n",
    "print(len(data_dict))\n",
    "print(data_dict.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "conv1_1 = data_dict['conv1_1']\n",
    "print(len(conv1_1))\n",
    "w, b = conv1_1\n",
    "print(w.shape)\n",
    "print(b.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fc6 = data_dict['fc6']\n",
    "print(len(fc6))\n",
    "w, b = fc6\n",
    "print(w.shape)\n",
    "print(b.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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