lstm_check_model_parameter_count.ipynb

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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "from keras import layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Nt = 4096\n",
    "Nx = 64\n",
    "Nh = 130\n",
    "\n",
    "model = keras.Sequential(\n",
    "    [\n",
    "    layers.Input(shape=(Nt, Nx)),\n",
    "    layers.LSTM(Nh, return_sequences=True)\n",
    "    ])\n",
    "model.summary()\n",
    "print(4 * Nh*Nx + 4 * Nh*Nh + 4 * Nh*1, 4 * Nh * (Nx + Nh + 1))\n",
    "\n",
    "model = keras.Sequential(\n",
    "    [\n",
    "    layers.Input(shape=(Nt, Nx)),\n",
    "    layers.Bidirectional(layers.LSTM(Nh, return_sequences=True))\n",
    "    ])\n",
    "model.summary()\n",
    "print(2 * (4 * Nh*Nx + 4 * Nh*Nh + 4 * Nh*1), 2 * 4 * Nh * (Nx + Nh + 1))\n"
   ]
  }
 ],
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