{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Recommending Movies\n",
    "\n",
    "This notebook will explore the possibility of learning a set of movie watchers' (the \"users\") preferences for a set of movies. We use a database that has a rating for each movie the user has seen. There are a few datasets available: \n",
    "\n",
    "https://grouplens.org/datasets/movielens/\n",
    "\n",
    "We will use the MovieLens 1M Dataset. It contains 1 million ratings from about 6000 users on about 4000 movies. Released 2/2003.\n",
    "\n",
    "https://grouplens.org/datasets/movielens/1m/\n",
    "\n",
    "Can we build a system that can learn to make recommendations for you?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook follows after the Keras example here: https://github.com/ririw/ririw.github.io/blob/master/assets/Recommending%20movies.ipynb\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using Theano backend.\n",
      "conx, version 3.5.9\n"
     ]
    }
   ],
   "source": [
    "import conx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we download the dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "format": "row"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using cached http://files.grouplens.org/datasets/movielens/ml-1m.zip as './ml-1m.zip'.\n",
      "Unzipping files...\n",
      "Done!\n",
      "Items available from downloaded zip file:\n",
      "     ./ml-1m/\n",
      "     ./ml-1m/movies.dat\n",
      "     ./ml-1m/ratings.dat\n",
      "     ./ml-1m/README\n",
      "     ./ml-1m/users.dat\n",
      "Available: 5 of 5.\n"
     ]
    }
   ],
   "source": [
    "conx.download(\"http://files.grouplens.org/datasets/movielens/ml-1m.zip\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use pandas to parse and read in the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Read in the dataset, and do a little preprocessing,\n",
    "# mostly to set the column datatypes.\n",
    "users = pandas.read_csv('./ml-1m/users.dat', sep='::', \n",
    "                        engine='python', \n",
    "                        names=['userid', 'gender', 'age', 'occupation', 'zip']).set_index('userid')\n",
    "ratings = pandas.read_csv('./ml-1m/ratings.dat', engine='python', \n",
    "                          sep='::', names=['userid', 'movieid', 'rating', 'timestamp'])\n",
    "movies = pandas.read_csv('./ml-1m/movies.dat', engine='python',\n",
    "                         sep='::', names=['movieid', 'title', 'genre']).set_index('movieid')\n",
    "movies['genre'] = movies.genre.str.split('|')\n",
    "\n",
    "users.age = users.age.astype('category')\n",
    "users.gender = users.gender.astype('category')\n",
    "users.occupation = users.occupation.astype('category')\n",
    "ratings.movieid = ratings.movieid.astype('category')\n",
    "ratings.userid = ratings.userid.astype('category')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We get the number of movies and users:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_movies = movies.shape[0]\n",
    "n_users = users.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3883, 6040)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_movies, n_users"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Designing the Dataset\n",
    "\n",
    "In order to making a recommendation system, we wish to training a neural network to take in a user id and a movie id, and learning to output the user's rating for that movie.\n",
    "\n",
    "Therefore, we need a list of movie ids, a list of user ids, and a list of the 1-5 ratings (called targets here):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Also, make vectors of all the movie ids and user ids. These are\n",
    "# pandas categorical data, so they range from 1 to n_movies and 1 to n_users, respectively.\n",
    "movie_ids = ratings.movieid.cat.codes.values\n",
    "user_ids = ratings.userid.cat.codes.values\n",
    "targets = ratings.rating.values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we make a dataset. Because this network will have two input banks (users and movies) we need to specify that to the dataset so that it knows how to interpret the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = conx.Dataset(name=\"Movie Recommendations\", input_shapes=[(1,), (1,)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we collect the [[movie_id], [user_id]] as inputs and the rating as a target. Note that we turn the 1-5 rating into a 0-4 value, and then make it a onehot representation. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "pairs = []\n",
    "for i in range(len(movie_ids)):\n",
    "    ins = [movie_ids[i]], [user_ids[i]]\n",
    "    targs = conx.onehot(targets[i] - 1, 5)\n",
    "    pairs.append([ins, targs])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "**Dataset name**: Movie Recommendations\n",
       "\n",
       "**Dataset Split**:\n",
       "   * training  : 1000209\n",
       "   * testing   : 0\n",
       "   * total     : 1000209\n",
       "\n",
       "**Input Summary**:\n",
       "   * shape  : [(1,), (1,)]\n",
       "   * range  : [(0.0, 3705.0), (0.0, 6039.0)]\n",
       "\n",
       "**Target Summary**:\n",
       "   * shape  : [(5,)]\n",
       "   * range  : [(0.0, 1.0)]\n",
       "\n"
      ],
      "text/plain": [
       "**Dataset name**: Movie Recommendations\n",
       "\n",
       "**Dataset Split**:\n",
       "   * training  : 1000209\n",
       "   * testing   : 0\n",
       "   * total     : 1000209\n",
       "\n",
       "**Input Summary**:\n",
       "   * shape  : [(1,), (1,)]\n",
       "   * range  : [(0.0, 3705.0), (0.0, 6039.0)]\n",
       "\n",
       "**Target Summary**:\n",
       "   * shape  : [(5,)]\n",
       "   * range  : [(0.0, 1.0)]\n"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.load(pairs)\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Designing the Network\n",
    "\n",
    "Because there are so many users and movies, we need a good way of representing them. In this example, we use an EmbeddingLayer. This will learn to represent users and movies in ways such that similar movies will have similar representations, and users with similar tastes will also have similar representations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
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MmfSrDlTAM6cOnfqBODzJ9CgQn1aKFoUBFIQF5YuDeE0hIOoUjFQpSriqogRWkdk6NqVBFgSGsaOLWG2xIO0ahOwZavgLVy4CeYmqGDX7oe8Hxrw7Uvh718Pgj1MKFy4A+IOEhYv5uCYA4PIkiNQprzh8gYImjUP6Oz5M2jPCEaTLj3aAOrU/6pXH2jt+nXrArJn06694DZuEwF28+7t2zeB4MKHExcu4Djy5MqTA2ju/Dn06M0tUKcO4jqIC9q1h+gewgH48BjGjxdhXsSI9CMysGdP4j0JDfLll6hf4gH+/An271fgH6ACgQMTFExQASHCDws/NHD4kELEiB4oephw8WIHjR0kdOzIASQHBiNJRjBpckPKDRBYshzwEmZMmTAR1LR5s6YBnTt59jzwE2jQnwWIFjV6dEFSpSYCNHX6FCpUAlOpVrVKVUBWrVu5bgXwFWxYsWO/WjBrFkRaEBfYsg3xNoQDuXMx1K0rAq+IEXtHZPDrl0RgEhoIEy5xuMQDxYsTNP9urABy5MgJKCeocPnyB80fGnT2TAE0aA+jPUwwbbpD6g4SWLPm8JoDA9mzI9SuvQH3Bgi7dw/w/Rt48N8IiBc3TtxAcuXLmR9w/hy68wLTqVe3vgB7dhMBuHf3/v07AfHjyZcfLwB9evXr1QNw/x5+fPnuLdSvDwI/iAv794fwDzCEg4EEMRg0KCKhiBEMR2R4+JCERBIaKlYsgbHEg40cE3j0qCCkSJEJSiaogBLlh5UfGrh8SSFmTA80PUy4ebODzg4SevbkAJQDg6FEIxg1uiHpBghMmQ54CjWqVKgIqlq9WtWA1q1cux74Cjbs1wJky5o9uyCtWhMB2rp9Cxf/LoG5dOvapSsgr969fPcC+As4sODBfy0YNgwiMYgLjBmHeBzCgeTJGCpXFoFZxIjNIzJ49kwiNAkNpEmXOF3igerVCVq3VgA7duwEtBNUuH37g+4PDXr7pgAcuIfhHiYYN94heQcJzJlzeM6BgfTpEapX34B9A4Tt2wd4/w4+/HcE5MubJ28gvfr17A+4fw/ffYH59OvbX4A/v4kA/Pv7BxhA4ECCBAweRJjwoACGDR0+dAhA4kSKFS1KtJAxIwiOIC58/BhCZAgHJU1iQIlSxEoRI1yOyBAzJgmaJDTcvFlCZ4kHPX0mAApUwVCiRBMcTVBBqdIPTT80gBqVwtSp4x6sepiQNWsHrh0kfP3KQSwHBmXNRkCLdsPaDRDcuh0QV+5cunIR3MWb964Bvn39/j0QWPDgwAUMH0aceMFixiYCPIYcWbJkApUtX8ZsWcBmzp09dwYQWvRo0qVDW0CNGsRqEBdcuw4RO4QD2rUx3L4tQreIEb1HZAAOnMRwEhqMGy+RvMQD5s0TPH+uQPr06QmsJ6iQPfsH7h8afAdPQbx4D+U9TECPvsP6DhLcu+cQnwMD+vUj3L+/Qf8GCP37AxwgcCDBggMRIEyoEKGBhg4fQjwgcSJFiQUuYsyocQHHjgEBADs=\"/>'), FloatText(value=-1.0, description='Leftmost color maps to:', style=DescriptionStyle(description_width='initial')), FloatText(value=1.0, description='Rightmost color maps to:', style=DescriptionStyle(description_width='initial')), IntText(value=0, description='Feature to show:', style=DescriptionStyle(description_width='initial'))), layout=Layout(width='100%')))),), selected_index=None, _titles={'0': 'Recommender'}), VBox(children=(HBox(children=(IntSlider(value=0, continuous_update=False, description='Dataset index', layout=Layout(width='100%'), max=0), Label(value='of 0', layout=Layout(width='100px'))), layout=Layout(height='40px')), HBox(children=(Button(icon='fast-backward', layout=Layout(width='100%'), style=ButtonStyle()), Button(icon='backward', layout=Layout(width='100%'), style=ButtonStyle()), IntText(value=0, layout=Layout(width='100%')), Button(icon='forward', layout=Layout(width='100%'), style=ButtonStyle()), Button(icon='fast-forward', layout=Layout(width='100%'), style=ButtonStyle()), Button(description='Play', icon='play', layout=Layout(width='100%'), style=ButtonStyle()), Button(icon='refresh', layout=Layout(width='25%'), style=ButtonStyle())), layout=Layout(height='50px', width='100%'))), layout=Layout(width='100%')), HTML(value='<p style=\"text-align:center\"></p>', layout=Layout(justify_content='center', overflow_x='auto', overflow_y='auto', width='95%')), Output()))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "require(['base/js/namespace'], function(Jupyter) {\n",
       "    Jupyter.notebook.kernel.comm_manager.register_target('conx_svg_control', function(comm, msg) {\n",
       "        comm.on_msg(function(msg) {\n",
       "            var data = msg[\"content\"][\"data\"];\n",
       "            var images = document.getElementsByClassName(data[\"class\"]);\n",
       "            for (var i = 0; i < images.length; i++) {\n",
       "                if (data[\"href\"]) {\n",
       "                    images[i].setAttributeNS(null, \"href\", data[\"href\"]);\n",
       "                }\n",
       "                if (data[\"src\"]) {\n",
       "                    images[i].setAttributeNS(null, \"src\", data[\"src\"]);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "    });\n",
       "});\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "require(['base/js/namespace'], function(Jupyter) {\n",
       "    Jupyter.notebook.kernel.comm_manager.register_target('conx_svg_control', function(comm, msg) {\n",
       "        comm.on_msg(function(msg) {\n",
       "            var data = msg[\"content\"][\"data\"];\n",
       "            var images = document.getElementsByClassName(data[\"class\"]);\n",
       "            for (var i = 0; i < images.length; i++) {\n",
       "                if (data[\"href\"]) {\n",
       "                    images[i].setAttributeNS(null, \"href\", data[\"href\"]);\n",
       "                }\n",
       "                if (data[\"src\"]) {\n",
       "                    images[i].setAttributeNS(null, \"src\", data[\"src\"]);\n",
       "                }\n",
       "            }\n",
       "        });\n",
       "    });\n",
       "});\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "net = conx.Network(\"Recommender\")\n",
    "net.add(conx.InputLayer(\"movie\", 1))\n",
    "net.add(conx.EmbeddingLayer(\"movie_embed\", n_movies + 1, 32))\n",
    "net.add(conx.FlattenLayer(\"movie_flatten\", dropout=0.5))\n",
    "net.add(conx.InputLayer(\"user\", 1))\n",
    "net.add(conx.EmbeddingLayer(\"user_embed\", n_users + 1, 32))\n",
    "net.add(conx.FlattenLayer(\"user_flatten\", dropout=0.5))\n",
    "net.add(conx.Layer(\"dense1\", 128, activation=\"relu\", dropout=0.5))\n",
    "net.add(conx.BatchNormalizationLayer(\"batch norm1\"))\n",
    "net.add(conx.Layer(\"dense2\", 128, activation=\"relu\", dropout=0.5))\n",
    "net.add(conx.BatchNormalizationLayer(\"batch norm2\"))\n",
    "net.add(conx.Layer(\"dense3\", 128, activation=\"relu\", dropout=0.5))\n",
    "net.add(conx.Layer(\"output\", 5, activation=\"softmax\"))\n",
    "\n",
    "net.connect(\"movie\", \"movie_embed\")\n",
    "net.connect(\"movie_embed\", \"movie_flatten\")\n",
    "net.connect(\"user\", \"user_embed\")\n",
    "net.connect(\"user_embed\", \"user_flatten\")\n",
    "net.connect(\"movie_flatten\", \"dense1\")\n",
    "net.connect(\"user_flatten\", \"dense1\")\n",
    "net.connect(\"dense1\", \"batch norm1\")\n",
    "net.connect(\"batch norm1\", \"dense2\")\n",
    "net.connect(\"dense2\", \"batch norm2\")\n",
    "net.connect(\"batch norm2\", \"dense3\")\n",
    "net.connect(\"dense3\", \"output\")\n",
    "\n",
    "net.compile(optimizer='adam', error='categorical_crossentropy')\n",
    "net.dashboard()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAAyCAYAAAB1V8bkAAAA1klEQVR4nO3TwQ2CABBFwcXYKQdq8kCteDCWQFDeTAX7s3nLzBwD3NpzZmbf/7v1dV1mZub1+u8d2/bZ4R+/4fuPO+x4XH0EcD6hQ4DQIUDoECB0CBA6BAgdAoQOAUKHAKFDgNAhQOgQIHQIEDoECB0ChA4BQocAoUOA0CFA6BAgdAgQOgQIHQKEDgFChwChQ4DQIUDoECB0CBA6BAgdAoQOAUKHAKFDgNAhQOgQIHQIEDoECB0ChA4BQocAoUOA0CFA6BAgdAgQOgQIHQKWmTmuPgI41xvvXhFjlRgMjwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=250x50 at 0x7FA2C54714E0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net.propagate_to_image(\"output\", [[1], [n_users]], visualize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "net.set_dataset(ds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Press the refresh button on the above dashboard to be able to examine the dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just practicing here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "net.dataset.chop(0.01) ## retain 1%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "**Dataset name**: Movie Recommendations\n",
       "\n",
       "**Dataset Split**:\n",
       "   * training  : 10002\n",
       "   * testing   : 0\n",
       "   * total     : 10002\n",
       "\n",
       "**Input Summary**:\n",
       "   * shape  : [(1,), (1,)]\n",
       "   * range  : [(0.0, 3705.0), (0.0, 6039.0)]\n",
       "\n",
       "**Target Summary**:\n",
       "   * shape  : [(5,)]\n",
       "   * range  : [(0.0, 1.0)]\n",
       "\n"
      ],
      "text/plain": [
       "**Dataset name**: Movie Recommendations\n",
       "\n",
       "**Dataset Split**:\n",
       "   * training  : 10002\n",
       "   * testing   : 0\n",
       "   * total     : 10002\n",
       "\n",
       "**Input Summary**:\n",
       "   * shape  : [(1,), (1,)]\n",
       "   * range  : [(0.0, 3705.0), (0.0, 6039.0)]\n",
       "\n",
       "**Target Summary**:\n",
       "   * shape  : [(5,)]\n",
       "   * range  : [(0.0, 1.0)]\n"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net.dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "net.dataset.split(.10) # save 10% for testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "**Dataset name**: Movie Recommendations\n",
       "\n",
       "**Dataset Split**:\n",
       "   * training  : 9002\n",
       "   * testing   : 1000\n",
       "   * total     : 10002\n",
       "\n",
       "**Input Summary**:\n",
       "   * shape  : [(1,), (1,)]\n",
       "   * range  : [(0.0, 3705.0), (0.0, 6039.0)]\n",
       "\n",
       "**Target Summary**:\n",
       "   * shape  : [(5,)]\n",
       "   * range  : [(0.0, 1.0)]\n",
       "\n"
      ],
      "text/plain": [
       "**Dataset name**: Movie Recommendations\n",
       "\n",
       "**Dataset Split**:\n",
       "   * training  : 9002\n",
       "   * testing   : 1000\n",
       "   * total     : 10002\n",
       "\n",
       "**Input Summary**:\n",
       "   * shape  : [(1,), (1,)]\n",
       "   * range  : [(0.0, 3705.0), (0.0, 6039.0)]\n",
       "\n",
       "**Target Summary**:\n",
       "   * shape  : [(5,)]\n",
       "   * range  : [(0.0, 1.0)]\n"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net.dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg height=\"288pt\" version=\"1.1\" viewBox=\"0 0 720 288\" width=\"720pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       " <defs>\n",
       "  <style type=\"text/css\">\n",
       "*{stroke-linecap:butt;stroke-linejoin:round;}\n",
       "  </style>\n",
       " </defs>\n",
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     "text": [
      "========================================================================\n",
      "       |  Training |  Training |  Validate |  Validate \n",
      "Epochs |     Error |  Accuracy |     Error |  Accuracy \n",
      "------ | --------- | --------- | --------- | --------- \n",
      "#   20 |   1.14289 |   0.00500 |   1.51707 |   0.00000 \n"
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   "source": [
    "net.train(epochs=20, plot=True)"
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   "source": [
    "net.propagate_to(\"movie_flatten\", net.dataset.inputs[0][0])"
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      "========================================================================\n",
      "       |  Training |  Training |  Validate |  Validate \n",
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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"52.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"104\" x2=\"350.0\" y2=\"77\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"104\" width=\"202\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_14\" class=\"Recommender_dense3\" x=\"250.0\" y=\"105\" height=\"50\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP78/QAATAAAzgQE9gAAh4WF/5WV/6Wl/8nJ/wAAcwAAuRUV/2lp/7S0/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIfAAHBAAgIMCBAA0UAAjAEAABAgAABABAEcAABAAMBABQAIAAACABBABAEkAAACgBBAAQAIDLAAICAJhJMwCABAAABADAE0AAAEABBBgKoOiAAAwAKF2KAIBTpwECAAiwQECAAAACAABQAMAAAAECGABAFkCAAAcCAFgbICAAOw==\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"132.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"184\" x2=\"350.0\" y2=\"157\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"184\" width=\"202\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_15\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"185\" height=\"50\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,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\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"212.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"264\" x2=\"350.0\" y2=\"237\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"264\" width=\"202\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_16\" class=\"Recommender_dense2\" x=\"250.0\" y=\"265\" height=\"50\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAAAATP/9/QIC9AAAagAAi+Pj/wAA3h0d/319/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIhQADAAgAAIAAAAACBABQAIDDAAEGAAgAgECAiwACBADAkQAAAAEAiAwAIACAkwEABAgA4ACAAAEABAAQoCaAmwAECAgAAECAAAAGBBgKAEAAAAECAAAQAACAAAYCAABQIEAAAAQADAgAIEAAAAIAiA0AoKzZAAAABAAAIAACAAACAAgAICAAOw==\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"292.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"344\" x2=\"350.0\" y2=\"317\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"344\" width=\"202\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_17\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"345\" height=\"50\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,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\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"372.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"424\" x2=\"350.0\" y2=\"397\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"424\" width=\"202\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_18\" class=\"Recommender_dense1\" x=\"250.0\" y=\"425\" height=\"50\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP37/eTk/6Oj/7i4/8nJ/4WF/5SU/9fX/3Z2/2Nj/yAg/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIgwABAEAAAECAAwAMEADAUAEBAAAEAJhIgMCAAQEOADgAoKNHjwEEEABAAECCAAIAqBQAAMCBAAkAyCxgwEAAAwAQABhQAIBPAAIAFABANACAAQAAIChAoACApwMKAAhQAIABAQAIANgKYAAAAAYGABgrIECAAwAGABBA4ACAAQAACAgIADs=\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"452.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"504\" x2=\"350.0\" y2=\"477\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"504\" width=\"202\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_19\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"505\" height=\"50\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv5/NfX//+5uezo+sfH/62t///Nzbm5///d3QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIJgABACgAgECAAQEEBEBAAMAAAAACDChwwICAiwYABBhAYICAAAEBADs=\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"532.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"504\" x2=\"350.0\" y2=\"477\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"504\" width=\"202\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_20\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"505\" height=\"50\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAP33+ffn79jY/8fH///X17m5//+xsf/IyAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIJgAHHAAwIEAAAAgFABAQIAAAAAIEAAAQwIAAAAQKBCAgIAAAAAEBADs=\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"532.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"584\" x2=\"233.33333333333334\" y2=\"557\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"584\" width=\"202\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_21\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"585\" height=\"50\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv5/NfX//+5uezo+sfH/62t///Nzbm5///d3QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIJgABACgAgECAAQEEBEBAAMAAAAACDChwwICAiwYABBhAYICAAAEBADs=\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"612.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"584\" x2=\"466.6666666666667\" y2=\"557\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"584\" width=\"202\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_22\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"585\" height=\"50\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAP33+ffn79jY/8fH///X17m5//+xsf/IyAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIJgAHHAAwIEAAAAgFABAQIAAAAAIEAAAQwIAAAAQKBCAgIAAAAAEBADs=\"><title>Layer: user_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"571.6666666666667\" y=\"612.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_embed</text><line x1=\"233.33333333333334\" y1=\"664\" x2=\"233.33333333333334\" y2=\"637\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie to movie_embed\n movie_embed/embeddings has shape (3884, 32)</title></line><rect x=\"207.33333333333334\" y=\"664\" width=\"52\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_23\" class=\"Recommender_movie\" x=\"208.33333333333334\" y=\"665\" height=\"50\" width=\"50\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,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\"><title>Layer: movie (input)\n shape = (1,)\n Keras class = Input\n dtype = int32</title></image><text x=\"263.33333333333337\" y=\"692.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie</text><line x1=\"466.6666666666667\" y1=\"664\" x2=\"466.6666666666667\" y2=\"637\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user to user_embed\n user_embed/embeddings has shape (6041, 32)</title></line><rect x=\"440.6666666666667\" y=\"664\" width=\"52\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_24\" class=\"Recommender_user\" x=\"441.6666666666667\" y=\"665\" height=\"50\" width=\"50\" preserveAspectRatio=\"none\" 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user (input)\n shape = (1,)\n Keras class = Input\n dtype = int32</title></image><text x=\"496.6666666666667\" y=\"692.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user</text></svg></p>"
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      "model_module": "@jupyter-widgets/controls",
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      "model_name": "DescriptionStyleModel",
      "state": {
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     "0de26838d887478497f7eefef243cc96": {
      "model_module": "@jupyter-widgets/base",
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      "model_name": "LayoutModel",
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     "0e86e1a0e3ac41f8a4aa618619b5e0af": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_8891f54c95ca4eecb3ab6085af1e3cbd",
        "IPY_MODEL_5d9f2f8864e44ed8b99f547266c692b3"
       ],
       "layout": "IPY_MODEL_5254bd4c5a614b398d553dc9f4e82f7f"
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     "0ea3cd50e55946bf8cc896853ca212c0": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "ButtonModel",
      "state": {
       "icon": "forward",
       "layout": "IPY_MODEL_f68f3d5e69e7468bb4d1406d74e0aaa8",
       "style": "IPY_MODEL_7b619b52e11d410bb5fa43fe0e4eb341"
      }
     },
     "0eb09152b33a4110a1a0956b2561939b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_93d41aecb1814d29add1240271247913",
       "style": "IPY_MODEL_768951b85c034405ab5e13cd2a4d2326",
       "value": "<p style=\"text-align:center\"><svg id='Recommender' xmlns='http://www.w3.org/2000/svg' viewBox=\"0 0 700 530.0\" max-width=\"100%\" height=\"780\" image-rendering=\"pixelated\">\n    <defs>\n        <marker id=\"arrow\" markerWidth=\"10\" markerHeight=\"10\" refX=\"9\" refY=\"3\" orient=\"auto\" markerUnits=\"strokeWidth\">\n          <path d=\"M0,0 L0,6 L9,3 z\" fill=\"black\" />\n        </marker>\n    </defs><text x=\"350.0\" y=\"12.5\" font-family=\"monospace\" font-size=\"15\" text-anchor=\"middle\" alignment-baseline=\"central\">Recommender</text><rect x=\"249.0\" y=\"24\" width=\"202\" height=\"42\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_output_1\" class=\"Recommender_output\" x=\"250.0\" y=\"25\" height=\"40\" width=\"200\" preserveAspectRatio=\"none\" 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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"94\" x2=\"350.0\" y2=\"67\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"94\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_2\" class=\"Recommender_dense3\" x=\"250.0\" y=\"95\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP38/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"109.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"149\" x2=\"350.0\" y2=\"122\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"149\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_3\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"150\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/e3t/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIHQABCBxIsKDBgwACAFjIsKHDhxAjSpxIsaJFiAEBADs=\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"164.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"204\" x2=\"350.0\" y2=\"177\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"204\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_4\" class=\"Recommender_dense2\" x=\"250.0\" y=\"205\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/e3t/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIHQABCBxIsKDBgwACAFjIsKHDhxAjSpxIsaJFiAEBADs=\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"219.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"259\" x2=\"350.0\" y2=\"232\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"259\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_5\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"260\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAILwABCBxIsKDBgwgTKkwYAIDDhxAfBgBAsaLFAAAyBggAoKPHjyA/BgBAsqTJkgEBADs=\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"274.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"314\" x2=\"350.0\" y2=\"287\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"314\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_6\" class=\"Recommender_dense1\" x=\"250.0\" y=\"315\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAILwABCBxIsKDBgwgTKkwYAIDDhxAfBgBAsaLFAAAyBggAoKPHjyA/BgBAsqTJkgEBADs=\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"329.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_7\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPz4+vrn7AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHQABBABAsGAAAAEABADAsCGAAAAiBgBAMYBFAAEBADs=\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_8\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr3/Pbp8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAADABgYAIBBgwECAAgAoGGAAAAiAggQAEAAAAEyBggIADs=\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"424\" x2=\"233.33333333333334\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_9\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPz4+vrn7AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHQABBABAsGAAAAEABADAsCGAAAAiBgBAMYBFAAEBADs=\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"424\" x2=\"466.6666666666667\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_10\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr3/Pbp8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAADABgYAIBBgwECAAgAoGGAAAAiAggQAEAAAAEyBggIADs=\"><title>Layer: user_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"571.6666666666667\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_embed</text><line x1=\"233.33333333333334\" y1=\"479\" x2=\"233.33333333333334\" y2=\"452\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie to movie_embed\n movie_embed/embeddings has shape (3884, 32)</title></line><rect x=\"219.83333333333334\" y=\"479\" width=\"27.0\" height=\"27.0\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_11\" class=\"Recommender_movie\" x=\"220.83333333333334\" y=\"480\" height=\"25.0\" width=\"25.0\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,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\"><title>Layer: movie (input)\n shape = (1,)\n Keras class = Input\n dtype = int32</title></image><text x=\"250.83333333333334\" y=\"494.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie</text><line x1=\"466.6666666666667\" y1=\"479\" x2=\"466.6666666666667\" y2=\"452\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user to user_embed\n user_embed/embeddings has shape (6041, 32)</title></line><rect x=\"453.1666666666667\" y=\"479\" width=\"27.0\" height=\"27.0\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_12\" class=\"Recommender_user\" x=\"454.1666666666667\" y=\"480\" height=\"25.0\" width=\"25.0\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,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\"><title>Layer: user (input)\n shape = (1,)\n Keras class = Input\n dtype = int32</title></image><text x=\"484.1666666666667\" y=\"494.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user</text></svg></p>"
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        "Blues",
        "Blues_r",
        "BrBG",
        "BrBG_r",
        "BuGn",
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        "BuPu",
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        "GnBu_r",
        "Greens",
        "Greens_r",
        "Greys",
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        "OrRd",
        "OrRd_r",
        "Oranges",
        "Oranges_r",
        "PRGn",
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        "Paired",
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        "Pastel1_r",
        "Pastel2",
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        "PiYG",
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        "PuBu_r",
        "PuOr",
        "PuOr_r",
        "PuRd",
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        "Purples",
        "Purples_r",
        "RdBu",
        "RdBu_r",
        "RdGy",
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        "RdPu",
        "RdPu_r",
        "RdYlBu",
        "RdYlBu_r",
        "RdYlGn",
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        "Set2",
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        "Spectral",
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        "afmhot",
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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">targets</text><rect x=\"249.0\" y=\"74\" width=\"202\" height=\"42\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_output_25\" class=\"Recommender_output\" x=\"250.0\" y=\"75\" height=\"40\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"97.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"144\" x2=\"350.0\" y2=\"117\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"144\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_26\" class=\"Recommender_dense3\" x=\"250.0\" y=\"145\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP38/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"159.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"199\" x2=\"350.0\" y2=\"172\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"199\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_27\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"200\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP37/e3t/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIHQABCBxIsKDBgwgTJgwAoKHDhxAjSpxIsaJFiQEBADs=\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"214.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"254\" x2=\"350.0\" y2=\"227\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"254\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_28\" class=\"Recommender_dense2\" x=\"250.0\" y=\"255\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP37/e3t/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIHQABCBxIsKDBgwgTJgwAoKHDhxAjSpxIsaJFiQEBADs=\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"269.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"309\" x2=\"350.0\" y2=\"282\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"309\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_29\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"310\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPv6/efn/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIJgABCBxIsKDBAAASKlzIUGEAABAjSpxIsaLFixgzaoQYAIDHjwEBADs=\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"324.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"364\" x2=\"350.0\" y2=\"337\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"364\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_30\" class=\"Recommender_dense1\" x=\"250.0\" y=\"365\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPv6/efn/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIJgABCBxIsKDBAAASKlzIUGEAABAjSpxIsaLFixgzaoQYAIDHjwEBADs=\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"379.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"419\" x2=\"350.0\" y2=\"392\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"419\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_31\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"420\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv3+vXq8wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHgABBBgYAACAAAASKgwQAEAAABADBABAsSKAAAACAgA7\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"434.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"419\" x2=\"350.0\" y2=\"392\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"419\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_32\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"420\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr3/PTq9AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIQABAAgAoGCAAAASKgwAIEAAAAEAAAgAAEAAAAEAaAQQEAA7\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"434.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"474\" x2=\"233.33333333333334\" y2=\"447\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"474\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_33\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"475\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv3+vXq8wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHgABBBgYAACAAAASKgwQAEAAABADBABAsSKAAAACAgA7\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"489.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"474\" x2=\"466.6666666666667\" y2=\"447\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"474\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_34\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"475\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr3/PTq9AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIQABAAgAoGCAAAASKgwAIEAAAAEAAAgAAEAAAAEAaAQQEAA7\"><title>Layer: user_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"571.6666666666667\" y=\"489.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_embed</text><line x1=\"233.33333333333334\" y1=\"529\" x2=\"233.33333333333334\" y2=\"502\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie to movie_embed\n movie_embed/embeddings has shape (3884, 32)</title></line><rect x=\"219.83333333333334\" y=\"529\" width=\"27.0\" height=\"27.0\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_35\" class=\"Recommender_movie\" x=\"220.83333333333334\" y=\"530\" height=\"25.0\" width=\"25.0\" preserveAspectRatio=\"none\" 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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"94\" x2=\"350.0\" y2=\"67\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"94\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_2\" class=\"Recommender_dense3\" x=\"250.0\" y=\"95\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP37/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"109.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"149\" x2=\"350.0\" y2=\"122\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"149\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_3\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"150\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/e3t/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIJwABCBxIsKDBgwcDAFjIsKHDhxAjSgwAoKLFAAAyatzIsaPHjxoDAgA7\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"164.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"204\" x2=\"350.0\" y2=\"177\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"204\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_4\" class=\"Recommender_dense2\" x=\"250.0\" y=\"205\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/e3t/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIJwABCBxIsKDBgwcDAFjIsKHDhxAjSgwAoKLFAAAyatzIsaPHjxoDAgA7\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"219.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"259\" x2=\"350.0\" y2=\"232\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"259\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_5\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"260\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz6/enp/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIPgADABhIsCDBAAASKlyoMEAAABAjAggAoKLFixgzatxYMQCAjyADABg5MgCAkyhTqjwZAIDLlzBfBgBAs2ZAADs=\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"274.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"314\" x2=\"350.0\" y2=\"287\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"314\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_6\" class=\"Recommender_dense1\" x=\"250.0\" y=\"315\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz6/enp/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIPgADABhIsCDBAAASKlyoMEAAABAjAggAoKLFixgzatxYMQCAjyADABg5MgCAkyhTqjwZAIDLlzBfBgBAs2ZAADs=\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"329.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_7\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr2+/fp8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHwABCAQQAEAAAAEAKFy4MEAAAAECAAAQAECAiwAABAQAOw==\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_8\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPnp7vv2+QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIgADBAAAIEAAAAgDBAAAIIBDhwAABAAQAEAAABgDAAAQICAAOw==\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"424\" x2=\"233.33333333333334\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_9\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr2+/fp8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHwABCAQQAEAAAAEAKFy4MEAAAAECAAAQAECAiwAABAQAOw==\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"424\" x2=\"466.6666666666667\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_10\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPnp7vv2+QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIgADBAAAIEAAAAgDBAAAIIBDhwAABAAQAEAAABgDAAAQICAAOw==\"><title>Layer: user_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"571.6666666666667\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_embed</text><line x1=\"233.33333333333334\" y1=\"479\" x2=\"233.33333333333334\" y2=\"452\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie to movie_embed\n movie_embed/embeddings has shape (3884, 32)</title></line><rect x=\"219.83333333333334\" y=\"479\" width=\"27.0\" height=\"27.0\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_11\" class=\"Recommender_movie\" x=\"220.83333333333334\" y=\"480\" height=\"25.0\" width=\"25.0\" preserveAspectRatio=\"none\" 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     },
     "4aeb5b81e1ab4d7eb1fe79d393fb5f16": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "HTMLModel",
      "state": {
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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"94\" x2=\"350.0\" y2=\"67\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"94\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_2\" class=\"Recommender_dense3\" x=\"250.0\" y=\"95\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP38/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"109.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"149\" x2=\"350.0\" y2=\"122\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"149\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_3\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"150\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/e3t/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIGgABCBxIsKDBgwgTKlzIsKHDhAEASJxIcWJAADs=\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"164.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"204\" x2=\"350.0\" y2=\"177\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"204\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_4\" class=\"Recommender_dense2\" x=\"250.0\" y=\"205\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/e3t/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIGgABCBxIsKDBgwgTKlzIsKHDhAEASJxIcWJAADs=\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"219.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"259\" x2=\"350.0\" y2=\"232\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"259\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_5\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"260\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/ejo/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIPAABCAwAoKDBgwgLBgDAkGEAABAjSpxIseLEAAAyatzIEUAAACBDggwAIACAkyhTqlzJMgCAAABiygQQEAA7\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"274.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"314\" x2=\"350.0\" y2=\"287\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"314\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_6\" class=\"Recommender_dense1\" x=\"250.0\" y=\"315\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/ejo/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIPAABCAwAoKDBgwgLBgDAkGEAABAjSpxIseLEAAAyatzIEUAAACBDggwAIACAkyhTqlzJMgCAAABiygQQEAA7\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"329.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_7\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAP35+/fp8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAABCAwAAEAAAAgRBgAAIEAAAAEiAgAQIAAAAAEyZgwIADs=\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_8\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv2+fnp7wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAABCBQYAACAAAASAggQAACAABABSAwAIACAiwACBAgIADs=\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"424\" x2=\"233.33333333333334\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_9\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAP35+/fp8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAABCAwAAEAAAAgRBgAAIEAAAAEiAgAQIAAAAAEyZgwIADs=\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"424\" x2=\"466.6666666666667\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_10\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" 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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"94\" x2=\"350.0\" y2=\"67\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"94\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_14\" class=\"Recommender_dense3\" x=\"250.0\" y=\"95\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP38/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"109.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"149\" x2=\"350.0\" y2=\"122\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"149\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_15\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"150\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"164.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"204\" x2=\"350.0\" y2=\"177\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"204\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_16\" class=\"Recommender_dense2\" x=\"250.0\" y=\"205\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"219.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"259\" x2=\"350.0\" y2=\"232\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"259\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_17\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"260\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/ejo/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAILAABCBxIsKDBgwgTDgwAoKHDhxAjPgwAoKLFixgzZgwAoKPHjyA/BgBAkmRAADs=\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"274.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"314\" x2=\"350.0\" y2=\"287\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"314\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_18\" class=\"Recommender_dense1\" x=\"250.0\" y=\"315\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/ejo/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAILAABCBxIsKDBgwgTDgwAoKHDhxAjPgwAoKLFixgzZgwAoKPHjyA/BgBAkmRAADs=\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"329.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_19\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv2+ffq8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHgABAAgQAACAAAAABAAQAIDDAAAiSgxAkSKAixcDAgA7\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_20\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr3+/bo8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIGwABBAgAoKDBgwgBBAgAAECAAAAABAgAAECAgAA7\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"424\" x2=\"233.33333333333334\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_21\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv2+ffq8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHgABAAgQAACAAAAABAAQAIDDAAAiSgxAkSKAixcDAgA7\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"424\" x2=\"466.6666666666667\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_22\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" 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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"94\" x2=\"350.0\" y2=\"67\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"94\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_62\" class=\"Recommender_dense3\" x=\"250.0\" y=\"95\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"109.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"149\" x2=\"350.0\" y2=\"122\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"149\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_63\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"150\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIMAABCAQQAACAAAASKlzIsKHDhgEASAwAoKLFixgrBgAAIACAjyBDihxJsqTJkyIDAgA7\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"164.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"204\" x2=\"350.0\" y2=\"177\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"204\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_64\" class=\"Recommender_dense2\" x=\"250.0\" y=\"205\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIMAABCAQQAACAAAASKlzIsKHDhgEASAwAoKLFixgrBgAAIACAjyBDihxJsqTJkyIDAgA7\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"219.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"259\" x2=\"350.0\" y2=\"232\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"259\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_65\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"260\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz6/ejo/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIOAABCBxIsKDBAAASKkwYAIDDhxABBABAMQCAixgzagwAoKPHjyA/BgBAsqTJkyhTqiQZAIDLlwEBADs=\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"274.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"314\" x2=\"350.0\" y2=\"287\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"314\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_66\" class=\"Recommender_dense1\" x=\"250.0\" y=\"315\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz6/ejo/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIOAABCBxIsKDBAAASKkwYAIDDhxABBABAMQCAixgzagwAoKPHjyA/BgBAsqTJkyhTqiQZAIDLlwEBADs=\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"329.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_67\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPz4+vro7QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAABBBgIAEAAAAgTBgAAIAAAAAEABAAQAIBFiwECAAgIADs=\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_68\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPfp8fz3+QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHwABBBgIoKDBAAAABFgIAECAAAAiBggAoGIAAAECBAQAOw==\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"424\" x2=\"233.33333333333334\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_69\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPz4+vro7QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAABBBgIAEAAAAgTBgAAIAAAAAEABAAQAIBFiwECAAgIADs=\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"424\" x2=\"466.6666666666667\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_70\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" 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YMmfSrGnzJk6ZAgQA6OnzJ9CgQocS9SlAAICkSpcyber0KVSlAgQAqGr1KtasWrdytSpAQICwYseSLWv2LFqxAgQAaOv2Ldy4cufSdStAAIC8evfy7ev3L2C9AgQAKGz4MOLEihczNixAAIDIkidTrmz5MmbJAgQE6Oz5M+jQokeT9ixAAIDU/6pXs27t+jVs1QIEAKht+zbu3Lp387YtQACA4MKHEy9u/Dhy4QIEAGju/Dn06NKnU3cuQECA7Nq3c+/u/Tt47QIEAChv/jz69OrXszcvQACA+PLn069v/z5++QIEAOjvHyAAgQMJFjR4EKFBAQIANHT4EGJEiRMpOhQgIEBGjRs5dvT4EaRGAQIAlDR5EmVKlStZmhQgAEBMmTNp1rR5E6dMAQIA9PT5E2hQoUOJ+hQgAEBSpUuZNnX6FKpSAQICVLV6FWtWrVu5WhUgAEBYsWPJljV7Fq1YAQIAtHX7Fm5cuXPpuhUgAEBevXv59vX7F7BeAYMJFzZ8GHFixYsZNw12/BhyZMmTKVe2XDkgADs=\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"94\" x2=\"350.0\" y2=\"67\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"94\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_2\" class=\"Recommender_dense3\" x=\"250.0\" y=\"95\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"109.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"149\" x2=\"350.0\" y2=\"122\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"149\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_3\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"150\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAILAABCBxIkGAAAAgTKlzIEGEAABAjSpxIsaLFiAEAaNQYAIDHjyBDihxJcmRAADs=\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"164.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"204\" x2=\"350.0\" y2=\"177\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"204\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_4\" class=\"Recommender_dense2\" x=\"250.0\" y=\"205\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAILAABCBxIkGAAAAgTKlzIEGEAABAjSpxIsaLFiAEAaNQYAIDHjyBDihxJcmRAADs=\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"219.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"259\" x2=\"350.0\" y2=\"232\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"259\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_5\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"260\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz6/evr/9nZ/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIRQADAAAQAIDBgwACAFi4MACAhxAjSpxIUUAAABgzBgDAsaPHjyBDAggAAEAAAChTqgQQAIDLAABiypw5MwCAmzcDANgZEAA7\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"274.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"314\" x2=\"350.0\" y2=\"287\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"314\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_6\" class=\"Recommender_dense1\" x=\"250.0\" y=\"315\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz6/evr/9nZ/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIRQADAAAQAIDBgwACAFi4MACAhxAjSpxIUUAAABgzBgDAsaPHjyBDAggAAEAAAChTqgQQAIDLAABiypw5MwCAmzcDANgZEAA7\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"329.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_7\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv4/PTq9AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAABCAwAIIDBAAACBAAAIACAAAAiAghAEUCAAAAyZgwIADs=\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_8\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAP33+fXp8gAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIQABBBgIAEAAAAgDKAQAIEAAAAECAJgYAIDFAAACBAAQEAA7\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"424\" x2=\"233.33333333333334\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_9\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv4/PTq9AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAABCAwAIIDBAAACBAAAIACAAAAiAghAEUCAAAAyZgwIADs=\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"424\" x2=\"466.6666666666667\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_10\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAP33+fXp8gAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIQABBBgIAEAAAAgDKAQAIEAAAAECAJgYAIDFAAACBAAQEAA7\"><title>Layer: user_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"571.6666666666667\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_embed</text><line x1=\"233.33333333333334\" y1=\"479\" x2=\"233.33333333333334\" y2=\"452\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie to movie_embed\n movie_embed/embeddings has shape (3884, 32)</title></line><rect x=\"219.83333333333334\" y=\"479\" width=\"27.0\" height=\"27.0\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_11\" class=\"Recommender_movie\" x=\"220.83333333333334\" y=\"480\" height=\"25.0\" width=\"25.0\" preserveAspectRatio=\"none\" 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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"94\" x2=\"350.0\" y2=\"67\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"94\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_2\" class=\"Recommender_dense3\" x=\"250.0\" y=\"95\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP38/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"109.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"149\" x2=\"350.0\" y2=\"122\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"149\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_3\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"150\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"164.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"204\" x2=\"350.0\" y2=\"177\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"204\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_4\" class=\"Recommender_dense2\" x=\"250.0\" y=\"205\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"219.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"259\" x2=\"350.0\" y2=\"232\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"259\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_5\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"260\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAILQABCBxIsKDBgwgTKgQQIACAhxAjSpxIMWIAABgzatyIMQCAjyBDBgBAsiTJgAA7\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"274.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"314\" x2=\"350.0\" y2=\"287\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"314\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_6\" class=\"Recommender_dense1\" x=\"250.0\" y=\"315\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAILQABCBxIsKDBgwgTKgQQIACAhxAjSpxIMWIAABgzatyIMQCAjyBDBgBAsiTJgAA7\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"329.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_7\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv3+vHq+AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHQABCAxAEEAAAAgRBgAQAECAAAAiSowYAIDFAAEBADs=\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_8\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAP34+vTq9QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIgADBABAkGCAAAACAFgYIAAAAAEABAgAIACAAAAABADAMSAAOw==\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"424\" x2=\"233.33333333333334\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_9\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPv3+vHq+AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHQABCAxAEEAAAAgRBgAQAECAAAAiSowYAIDFAAEBADs=\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"424\" x2=\"466.6666666666667\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_10\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" 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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"94\" x2=\"350.0\" y2=\"67\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"94\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_2\" class=\"Recommender_dense3\" x=\"250.0\" y=\"95\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP38/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"109.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"149\" x2=\"350.0\" y2=\"122\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"149\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_3\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"150\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/eHh/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIGAABCBxIsKDBgwgTKlzIsKHDhwUDAAAQEAA7\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"164.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"204\" x2=\"350.0\" y2=\"177\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"204\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_4\" class=\"Recommender_dense2\" x=\"250.0\" y=\"205\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/eHh/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIGAABCBxIsKDBgwgTKlzIsKHDhwUDAAAQEAA7\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"219.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"259\" x2=\"350.0\" y2=\"232\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"259\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_5\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"260\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPv6/ejo/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIKgABCBwYAIDBgwgTKjwYAIBDAAEASJxIsaLFixgzasQYAIDHjyBDihQZEAA7\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"274.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"314\" x2=\"350.0\" y2=\"287\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"314\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_6\" class=\"Recommender_dense1\" x=\"250.0\" y=\"315\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPv6/ejo/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIKgABCBwYAIDBgwgTKjwYAIBDAAEASJxIsaLFixgzasQYAIDHjyBDihQZEAA7\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"329.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_7\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr3+/vr7wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHwABBAgAoGCAAAASJgwQAIDDhwEAAAgQAIDFAAAABAQAOw==\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_8\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr4/Pbq8wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHwADBABAsGAAAAACAFgYoCGAhw8DBAAAIEAAAAECBAQAOw==\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"424\" x2=\"233.33333333333334\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_9\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr3+/vr7wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHwABBAgAoGCAAAASJgwQAIDDhwEAAAgQAIDFAAAABAQAOw==\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"424\" x2=\"466.6666666666667\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_10\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" 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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"94\" x2=\"350.0\" y2=\"67\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"94\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_74\" class=\"Recommender_dense3\" x=\"250.0\" y=\"95\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/e3t/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIHQABCBxIsKDBgwgTKlyoMACAhxAjSpxIsaLFiQEBADs=\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"109.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"149\" x2=\"350.0\" y2=\"122\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"149\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_75\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"150\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIIAABCBxIUGAAAAgTKlzIsKHDhxAjSpwYMQCAixgzXgwIADs=\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"164.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"204\" x2=\"350.0\" y2=\"177\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"204\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_76\" class=\"Recommender_dense2\" x=\"250.0\" y=\"205\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIIAABCBxIUGAAAAgTKlzIsKHDhxAjSpwYMQCAixgzXgwIADs=\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"219.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"259\" x2=\"350.0\" y2=\"232\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"259\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_77\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"260\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/enp/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIRQADABg4MACAgwcDAFjIsKFDAAEASJxIsaLFixgzTgwAAEAAACBDAggAoKTJkgEAqFwZAIDLAAAABABAsyaAAABy6gQQEAA7\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"274.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"314\" x2=\"350.0\" y2=\"287\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"314\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_78\" class=\"Recommender_dense1\" x=\"250.0\" y=\"315\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/enp/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIRQADABg4MACAgwcDAFjIsKFDAAEASJxIsaLFixgzTgwAAEAAACBDAggAoKTJkgEAqFwZAIDLAAAABABAsyaAAABy6gQQEAA7\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"329.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_79\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPjq8Pv3+wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHgABCAwAoGCAgwACAFgYoCGAAAACSJQIIACAiwACAgA7\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_80\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPn2+/nq7wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHwABBAAAIIBBAAgDAAAQAACAABABSAwAoGLFAAAyBgQAOw==\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"424\" x2=\"233.33333333333334\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_81\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPjq8Pv3+wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIHgABCAwAoGCAgwACAFgYoCGAAAACSJQIIACAiwACAgA7\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"424\" x2=\"466.6666666666667\" y2=\"397\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"424\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_82\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"425\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" 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user_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"571.6666666666667\" y=\"439.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_embed</text><line x1=\"233.33333333333334\" y1=\"479\" x2=\"233.33333333333334\" y2=\"452\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie to movie_embed\n movie_embed/embeddings has shape (3884, 32)</title></line><rect x=\"219.83333333333334\" y=\"479\" width=\"27.0\" height=\"27.0\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_83\" class=\"Recommender_movie\" x=\"220.83333333333334\" y=\"480\" height=\"25.0\" width=\"25.0\" preserveAspectRatio=\"none\" 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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"94\" x2=\"350.0\" y2=\"67\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"94\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_14\" class=\"Recommender_dense3\" x=\"250.0\" y=\"95\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"109.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"149\" x2=\"350.0\" y2=\"122\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"149\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_15\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"150\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIKAABCBxIsKDBgwgTBgDAsKHDhgEABABAsaLFixgzatzIEWMAACABBAQAOw==\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"164.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"204\" x2=\"350.0\" y2=\"177\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"204\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_16\" class=\"Recommender_dense2\" x=\"250.0\" y=\"205\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIKAABCBxIsKDBgwgTBgDAsKHDhgEABABAsaLFixgzatzIEWMAACABBAQAOw==\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"219.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"259\" x2=\"350.0\" y2=\"232\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"259\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_17\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"260\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/enp/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAISAABCBw4MACAgwgBBADAMACAhwEASJxIsaLFAAAyagQQAIDHjx8DABhJsqTJkyYDAAgAoKXLAAEAyAQQAIDNmzYDANjJs2eAgAA7\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"274.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"314\" x2=\"350.0\" y2=\"287\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"314\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_18\" class=\"Recommender_dense1\" x=\"250.0\" y=\"315\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/enp/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAISAABCBw4MACAgwgBBADAMACAhwEASJxIsaLFAAAyagQQAIDHjx8DABhJsqTJkyYDAAgAoKXLAAEAyAQQAIDNmzYDANjJs2eAgAA7\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"329.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_19\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPj1+/jo7wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIJAADAAAQIACAAAAABAgAAECAhwEASAQQIAAAAAEAAAgAAECAgAA7\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"384.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"369\" x2=\"350.0\" y2=\"342\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"369\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_20\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"370\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr2+/fr8wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIQABAAgAIEAAAAgTAggAoGHDAAACAAAQIAAAAAEAAAgQEAA7\"><title>Layer: 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output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"47.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">targets</text><rect x=\"249.0\" y=\"74\" width=\"202\" height=\"42\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_output_25\" class=\"Recommender_output\" x=\"250.0\" y=\"75\" height=\"40\" width=\"200\" preserveAspectRatio=\"none\" 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\"><title>Layer: output (output)\n shape = (5,)\n Keras class = Dense\n activation = softmax</title></image><text x=\"455.0\" y=\"97.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">output</text><line x1=\"350.0\" y1=\"144\" x2=\"350.0\" y2=\"117\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense3 to output\n output/kernel has shape (128, 5)\n output/bias has shape (5,)</title></line><rect x=\"249.0\" y=\"144\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense3_26\" class=\"Recommender_dense3\" x=\"250.0\" y=\"145\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP78/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense3 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"159.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense3</text><line x1=\"350.0\" y1=\"199\" x2=\"350.0\" y2=\"172\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm2 to dense3\n dense3/kernel has shape (128, 128)\n dense3/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"199\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm2_27\" class=\"Recommender_batch norm2\" x=\"250.0\" y=\"200\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP38/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: batch norm2 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"214.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm2</text><line x1=\"350.0\" y1=\"254\" x2=\"350.0\" y2=\"227\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense2 to batch norm2\n batch norm2/gamma has shape (128,)\n batch norm2/beta has shape (128,)\n batch norm2/moving_mean has shape (128,)\n batch norm2/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"254\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense2_28\" class=\"Recommender_dense2\" x=\"250.0\" y=\"255\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAP38/QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIFQABCBxIsKDBgwgTKlzIsKHDhwgDAgA7\"><title>Layer: dense2 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"269.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense2</text><line x1=\"350.0\" y1=\"309\" x2=\"350.0\" y2=\"282\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from batch norm1 to dense2\n dense2/kernel has shape (128, 128)\n dense2/bias has shape (128,)</title></line><rect x=\"249.0\" y=\"309\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_batch norm1_29\" class=\"Recommender_batch norm1\" x=\"250.0\" y=\"310\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIOwABCAwAoGAAAAgRBgDAsKHDhwEASJwYAIDFixgzBgDAMQCAjyBBBgBAsqTJkyYDAFjJsqXLlzBjugwIADs=\"><title>Layer: batch norm1 (hidden)\n Keras class = BatchNormalization</title></image><text x=\"455.0\" y=\"324.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">batch norm1</text><line x1=\"350.0\" y1=\"364\" x2=\"350.0\" y2=\"337\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from dense1 to batch norm1\n batch norm1/gamma has shape (128,)\n batch norm1/beta has shape (128,)\n batch norm1/moving_mean has shape (128,)\n batch norm1/moving_variance has shape (128,)</title></line><rect x=\"249.0\" y=\"364\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_dense1_30\" class=\"Recommender_dense1\" x=\"250.0\" y=\"365\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhgAABAIcAAPz7/evr/wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAgAABAAAIOwABCAwAoGAAAAgRBgDAsKHDhwEASJwYAIDFixgzBgDAMQCAjyBBBgBAsqTJkyYDAFjJsqXLlzBjugwIADs=\"><title>Layer: dense1 (hidden)\n shape = (128,)\n dropout = 0.5\n Keras class = Dense\n activation = relu</title></image><text x=\"455.0\" y=\"379.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">dense1</text><line x1=\"233.33333333333334\" y1=\"419\" x2=\"350.0\" y2=\"392\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"132.33333333333334\" y=\"419\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_flatten_31\" class=\"Recommender_movie_flatten\" x=\"133.33333333333334\" y=\"420\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr2+vbp8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAADABgIIAAAAAECAAAQAACAABADAAgQAIDFiwEAaAwIADs=\"><title>Layer: movie_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"338.33333333333337\" y=\"434.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_flatten</text><line x1=\"466.6666666666667\" y1=\"419\" x2=\"350.0\" y2=\"392\" stroke=\"red\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_flatten to dense1\n dense1/kernel has shape (64, 128)\n dense1/bias has shape (128,)</title></line><rect x=\"365.6666666666667\" y=\"419\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_flatten_32\" class=\"Recommender_user_flatten\" x=\"366.6666666666667\" y=\"420\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPf1/Pnq8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIGwABCBwYAECAAAASKkwYAACAAAAiRgwQAIDFgAA7\"><title>Layer: user_flatten (hidden)\n dropout = 0.5\n Keras class = Flatten</title></image><text x=\"571.6666666666667\" y=\"434.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_flatten</text><line x1=\"233.33333333333334\" y1=\"474\" x2=\"233.33333333333334\" y2=\"447\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie_embed to movie_flatten</title></line><rect x=\"132.33333333333334\" y=\"474\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_embed_33\" class=\"Recommender_movie_embed\" x=\"133.33333333333334\" y=\"475\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPr2+vbp8QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIIAADABgIIAAAAAECAAAQAACAABADAAgQAIDFiwEAaAwIADs=\"><title>Layer: movie_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"338.33333333333337\" y=\"489.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">movie_embed</text><line x1=\"466.6666666666667\" y1=\"474\" x2=\"466.6666666666667\" y2=\"447\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from user_embed to user_flatten</title></line><rect x=\"365.6666666666667\" y=\"474\" width=\"202\" height=\"27\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_user_embed_34\" class=\"Recommender_user_embed\" x=\"366.6666666666667\" y=\"475\" height=\"25\" width=\"200\" preserveAspectRatio=\"none\" href=\"data:image/gif;base64,R0lGODdhIAABAIcAAPf1/Pnq8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwAAAAAIAABAAAIGwABCBwYAECAAAASKkwYAACAAAAiRgwQAIDFgAA7\"><title>Layer: user_embed (hidden)\n shape = (1, 32)\n Keras class = Dense</title></image><text x=\"571.6666666666667\" y=\"489.5\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">user_embed</text><line x1=\"233.33333333333334\" y1=\"529\" x2=\"233.33333333333334\" y2=\"502\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from movie to movie_embed\n movie_embed/embeddings has shape (3884, 32)</title></line><rect x=\"219.83333333333334\" y=\"529\" width=\"27.0\" height=\"27.0\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"Recommender_movie_35\" class=\"Recommender_movie\" x=\"220.83333333333334\" y=\"530\" height=\"25.0\" width=\"25.0\" preserveAspectRatio=\"none\" 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