How to restore CUDNNLSTM of TensorFlow at CPU device? So that it could be used in GPU, CPU or Mobile

check_model_at_cpy.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_layers = 1\n",
    "num_units = 128\n",
    "direction = \"bidirectional\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from cudnn_cpu_bi_trans/model_1\n"
     ]
    }
   ],
   "source": [
    "inputs    = tf.placeholder(tf.float32, [None, None, 32], name=\"inputs\")\n",
    "with tf.variable_scope(\"cudnn_lstm\"):\n",
    "    single_cell = lambda: tf.contrib.cudnn_rnn.CudnnCompatibleLSTMCell(num_units)\n",
    "    cells_fw = [single_cell() for _ in range(num_layers)]\n",
    "    cells_bw = [single_cell() for _ in range(num_layers)]\n",
    "    # Leave the scope arg unset.\n",
    "    (outputs, output_state_fw,\n",
    "    output_state_bw) = tf.contrib.rnn.stack_bidirectional_dynamic_rnn(cells_fw, cells_bw, inputs,dtype=tf.float32)\n",
    "\n",
    "    saver = tf.train.Saver()\n",
    "# Create session\n",
    "sess = tf.Session()\n",
    "# Restores\n",
    "saver.restore(sess, 'cudnn_cpu_bi_trans/model_1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "out = sess.run(outputs, {inputs: np.zeros([10,100,32])})"
   ]
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     "metadata": {},
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    "out.su"
   ]
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   "execution_count": null,
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   "source": []
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restore_cudnn.ipynb