{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LSTM model training notebook\n",
    "### Introduction\n",
    "IN this notebook, we are going to \n",
    "1. build a sine wave generator that is able to generate sine wave with noise, and anomalies\n",
    "2. train a LSTM model to predict the next timestamp's reading based on the previous readings\n",
    "3. validate the accuracy of our model\n",
    "4. save / reload this model\n",
    "\n",
    "This is a straightforward model that only predict a single dimension sinewave with slight noise. For more complicated production data, you can consider multi-dimensinoal input with more layers and hidden states."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.6.0\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "%matplotlib inline\n",
    "\n",
    "if torch.cuda.is_available():  \n",
    "    comput_dev = \"cuda:0\" \n",
    "else:  \n",
    "    comput_dev = \"cpu\"\n",
    "device = torch.device(comput_dev)\n",
    "print(torch.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data generation: Generate Sine Wave Pattern"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sine wave\n",
    "SR = 20 # number of sample in one period\n",
    "Visualize_Periods = 3 # number of periods for visualization\n",
    "seq_lenth = 1000 # sequence length\n",
    "batch_size = 20 # number of batches\n",
    "noise = 0.5 # noise level in data\n",
    "\n",
    "class sine_wave_obj:\n",
    "    def __init__(self, SR=40):\n",
    "        self.SR = SR\n",
    "        self.re_generate()\n",
    "    def plot(self):\n",
    "        # Plot\n",
    "        plt.plot(self.signal[0, :SR*Visualize_Periods])\n",
    "        plt.plot(self.disturbed_signal[0, :SR*Visualize_Periods])\n",
    "        plt.plot(self.signal[1, :SR*Visualize_Periods])\n",
    "        plt.plot(self.disturbed_signal[1, :SR*Visualize_Periods])\n",
    "        plt.xlabel('Time (s)')\n",
    "        plt.ylabel('Current (A)')\n",
    "        plt.show()\n",
    "        plt.plot(self.final[0, :SR*Visualize_Periods])\n",
    "        plt.xlabel('Time (s)')\n",
    "        plt.ylabel('Current Normalized (A)')\n",
    "        plt.show()\n",
    "        nor, abn = self.re_generate_abnormal_single()\n",
    "        plt.plot(nor.cpu()[:SR*Visualize_Periods])\n",
    "        plt.plot(abn.cpu()[:SR*Visualize_Periods])\n",
    "        plt.xlabel('Time (s)')\n",
    "        plt.ylabel('Current Normalized (A)')\n",
    "        plt.show()\n",
    "    def re_generate(self):\n",
    "        self.rand_init = np.random.randint(self.SR, size=batch_size)\n",
    "        self.t = np.array([range(0, seq_lenth),]*batch_size) + self.rand_init[:, np.newaxis]\n",
    "        self.scaler = MinMaxScaler(feature_range=(-1, 1))\n",
    "        self.signal = np.sin(2*np.pi/self.SR*self.t) * 10\n",
    "        self.disturbed_signal = self.signal + np.random.normal(0, noise, (batch_size, seq_lenth))\n",
    "        self.final = self.scaler.fit_transform(self.disturbed_signal.T).T\n",
    "        return torch.FloatTensor(self.final).to(device)\n",
    "    def re_generate_single(self):\n",
    "        self.re_generate()\n",
    "        temp =  self.disturbed_signal[0, :]\n",
    "        temp_final = self.scaler.fit_transform(temp.reshape(-1, 1))\n",
    "        return torch.FloatTensor(temp_final.flatten()).to(device)\n",
    "    def re_generate_abnormal_single(self):\n",
    "        normal = self.re_generate_single()\n",
    "        abnormal = normal.clone()\n",
    "#         # some zero\n",
    "#         abnormal[20:40] = 0\n",
    "        # out of phase\n",
    "        abnormal = abnormal[:13].repeat(100)[:1000]\n",
    "#         # upward trend\n",
    "#         abnormal += torch.range(start = 0, end = 9.99, step=0.01).to(device)\n",
    "        return normal, abnormal\n",
    "sine_wave = sine_wave_obj(SR)\n",
    "sine_wave.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Building: Define LSTM model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class LSTM(nn.Module):\n",
    "    def __init__(self, input_size=1, hidden_layer_size=50, output_size=1, layers = 1):\n",
    "        super().__init__()\n",
    "        self.hidden_layer_size = hidden_layer_size\n",
    "        self.input_size = input_size\n",
    "        self.lstm = nn.LSTM(input_size, self.hidden_layer_size, num_layers=layers).to(device)\n",
    "        self.linear = nn.Linear(hidden_layer_size, output_size).to(device)\n",
    "\n",
    "    def forward(self, input_seq):\n",
    "        lstm_out, _ = self.lstm(input_seq)\n",
    "        predictions = self.linear(lstm_out)\n",
    "        return predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = LSTM()\n",
    "model.to(device)\n",
    "loss_function = nn.MSELoss()\n",
    "optimizer = torch.optim.LBFGS(model.parameters(), lr=0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Training: Generate noisy data and feed into model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "curr_loss 0.00010062013461720198\n",
      "curr_loss 0.00011637561692623422\n",
      "curr_loss 0.00011429023288656026\n",
      "curr_loss 0.00013026408851146698\n",
      "curr_loss 9.510778181720525e-05\n",
      "curr_loss 0.00015451940998900682\n",
      "curr_loss 0.00014223152538761497\n",
      "curr_loss 0.0001521902740933001\n",
      "curr_loss 8.569611236453056e-05\n",
      "curr_loss 0.00012186996173113585\n",
      "epoch:   0 loss: 0.00012187\n",
      "curr_loss 8.694118878338486e-05\n",
      "curr_loss 0.00014480241225101054\n",
      "curr_loss 0.00014020003436598927\n",
      "curr_loss 0.00010043764632428065\n",
      "curr_loss 0.00013858525198884308\n",
      "curr_loss 0.00011059270036639646\n",
      "curr_loss 0.00015883099695201963\n",
      "curr_loss 0.00011916667426703498\n",
      "curr_loss 0.00010618288797559217\n",
      "curr_loss 0.00013539142673835158\n",
      "epoch:   1 loss: 0.00013539\n",
      "curr_loss 8.946745219873264e-05\n",
      "curr_loss 0.0001232640352100134\n",
      "curr_loss 0.00010655319056240842\n",
      "curr_loss 0.00012718224024865776\n",
      "curr_loss 0.00011127661855425686\n",
      "curr_loss 0.00011885399726452306\n",
      "curr_loss 0.00016183598199859262\n",
      "curr_loss 0.0001473239972256124\n",
      "curr_loss 0.00010472772555658594\n",
      "curr_loss 0.00012204359518364072\n",
      "epoch:   2 loss: 0.00012204\n",
      "curr_loss 9.82511046458967e-05\n",
      "curr_loss 0.00013163757103029639\n",
      "curr_loss 9.324644634034485e-05\n",
      "curr_loss 7.820303289918229e-05\n",
      "curr_loss 0.00010621098772389814\n",
      "curr_loss 0.0001218242323375307\n",
      "curr_loss 0.0001360329770250246\n",
      "curr_loss 9.853412484517321e-05\n",
      "curr_loss 0.00012854483793489635\n",
      "curr_loss 0.0001363316987408325\n",
      "epoch:   3 loss: 0.00013633\n",
      "curr_loss 0.00012976503057871014\n",
      "curr_loss 0.00010164454579353333\n",
      "curr_loss 0.00014518153329845518\n",
      "curr_loss 0.00011488833843031898\n",
      "curr_loss 0.00010877832391997799\n",
      "curr_loss 0.00013020246115047485\n",
      "curr_loss 9.659420175012201e-05\n",
      "curr_loss 0.00015081302262842655\n",
      "curr_loss 9.752297046361491e-05\n",
      "curr_loss 9.711973689263687e-05\n",
      "epoch:   4 loss: 0.00009712\n",
      "curr_loss 0.00010624501010170206\n",
      "curr_loss 0.00012870731006842107\n",
      "curr_loss 0.00012182511272840202\n",
      "curr_loss 0.00013126734120305628\n",
      "curr_loss 0.00012951987446285784\n",
      "curr_loss 0.00013738902634941041\n",
      "curr_loss 9.983554627979174e-05\n",
      "curr_loss 0.00016027876699808985\n",
      "curr_loss 0.00012907352356705815\n",
      "curr_loss 0.00011618358257692307\n",
      "epoch:   5 loss: 0.00011618\n",
      "curr_loss 0.0001403102360200137\n",
      "curr_loss 0.00012493174290284514\n",
      "curr_loss 0.00012318967492319643\n",
      "curr_loss 0.00012066817726008594\n",
      "curr_loss 9.589608816895634e-05\n",
      "curr_loss 9.583636710885912e-05\n",
      "curr_loss 0.00010488874249858782\n",
      "curr_loss 9.943763143382967e-05\n",
      "curr_loss 0.0001325561897829175\n",
      "curr_loss 0.00011319205077597871\n",
      "epoch:   6 loss: 0.00011319\n",
      "curr_loss 0.00010413162090117112\n",
      "curr_loss 0.00013743627641815692\n",
      "curr_loss 0.0001320579758612439\n",
      "curr_loss 0.00013975011825095862\n",
      "curr_loss 9.657926420914009e-05\n",
      "curr_loss 9.927103383233771e-05\n",
      "curr_loss 0.00011247759539401159\n",
      "curr_loss 0.00010011634003603831\n",
      "curr_loss 0.00013239656982477754\n",
      "curr_loss 0.00011949131294386461\n",
      "epoch:   7 loss: 0.00011949\n",
      "curr_loss 0.00013678311370313168\n",
      "curr_loss 0.00011942596756853163\n",
      "curr_loss 0.00010468915570527315\n",
      "curr_loss 0.00014156586257740855\n",
      "curr_loss 0.00011910999455722049\n",
      "curr_loss 0.00012956028513144702\n",
      "curr_loss 0.00010528514394536614\n",
      "curr_loss 9.831628995016217e-05\n",
      "curr_loss 0.00013132240565028042\n",
      "curr_loss 0.00011688461381709203\n",
      "epoch:   8 loss: 0.00011688\n",
      "curr_loss 7.616000948473811e-05\n",
      "curr_loss 0.0001105547635233961\n",
      "curr_loss 0.00010184919665334746\n",
      "curr_loss 0.00010317574924556538\n",
      "curr_loss 0.00010209419997408986\n",
      "curr_loss 0.00011537770478753373\n",
      "curr_loss 9.44446655921638e-05\n",
      "curr_loss 0.00011961528070969507\n",
      "curr_loss 0.00013486812531482428\n",
      "curr_loss 0.00011877046927111223\n",
      "epoch:   9 loss: 0.00011877\n",
      "epoch:   9 loss: 0.0001187705\n"
     ]
    }
   ],
   "source": [
    "epochs = 10\n",
    "epoch_size = 10\n",
    "curr_loss = 0\n",
    "optimizer = torch.optim.LBFGS(model.parameters(), lr=0.01)\n",
    "for i in range(epochs):\n",
    "    for j in range(epoch_size):\n",
    "        readings = sine_wave.re_generate().transpose(0,1)\n",
    "        readings_data = readings.view(seq_lenth ,batch_size, 1)[:-1, :, :]\n",
    "        readings_labels = readings.view(seq_lenth ,batch_size, 1)[1:, :, :]\n",
    "        def closure():\n",
    "            global curr_loss\n",
    "            global optimizer\n",
    "            optimizer.zero_grad()\n",
    "            y_pred = model(readings_data)\n",
    "            single_loss = loss_function(y_pred, readings_labels)\n",
    "            curr_loss = single_loss\n",
    "            single_loss.backward()\n",
    "            return single_loss\n",
    "        optimizer.step(closure)\n",
    "        print('curr_loss', curr_loss.item())\n",
    "    if i%1 == 0:\n",
    "        msg = f'epoch: {i:3} loss: {curr_loss.item():10.8f}'\n",
    "        print(msg)\n",
    "        with open('./training_log.txt', 'a+') as f:\n",
    "            f.write(msg + '\\n')\n",
    "\n",
    "print(f'epoch: {i:3} loss: {curr_loss.item():10.10f}')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Testing:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualize waveforms with anomaly and withouth anomaly by plotting the noarmalizaed output. \n",
    "The first diagram shows sinewave with slight noise and LSTM prediction, but no anomamaly. The second diagram shows sinewave with anomaly and LSTM prediction. The anomaly can be chosen from the waveform generator by commenting out other anomaly options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1000])\n",
      "Normal reading loss: 0.005610866006463766\n",
      "0.005610866006463766\n",
      "Abnormal reading loss: 0.09801285713911057\n",
      "(999,)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# model.eval()\n",
    "test_readings, test_abnormal_readings = sine_wave.re_generate_abnormal_single()\n",
    "print(test_readings.shape)\n",
    "\n",
    "# normal reading\n",
    "test_readings_data = test_readings.view(seq_lenth ,1, 1)[:-1, :, :]\n",
    "test_readings_labels = test_readings.view(seq_lenth ,1, 1)[1:, :, :]\n",
    "test_pred = model(test_readings_data)\n",
    "# print(test_pred[0:5], test_readings_labels[0:5])\n",
    "single_loss = loss_function(test_pred, test_readings_labels)\n",
    "print('Normal reading loss: {}'.format(single_loss.item()))\n",
    "print(single_loss.item())\n",
    "# abnormal reading\n",
    "test_ab_readings_data = test_abnormal_readings.view(seq_lenth ,1, 1)[:-1, :, :]\n",
    "test_ab_readings_labels = test_abnormal_readings.view(seq_lenth ,1, 1)[1:, :, :]\n",
    "test_ab_pred = model(test_ab_readings_data)\n",
    "single_ab_loss = loss_function(test_ab_pred, test_ab_readings_labels)\n",
    "print('Abnormal reading loss: {}'.format(single_ab_loss.item()))\n",
    "\n",
    "\n",
    "y_normal = test_pred.cpu().detach().numpy().flatten()\n",
    "y_abnormal = test_ab_pred.cpu().detach().numpy().flatten()\n",
    "print(y_normal.shape)\n",
    "\n",
    "plt.figure(figsize=(10,5))\n",
    "plt.grid(True)\n",
    "plt.title('Normal data, Anomaly score: {}'.format(single_loss.item()))\n",
    "plt.autoscale(axis='x', tight=True)\n",
    "normal_real, = plt.plot(test_readings_labels.cpu().view(seq_lenth-1)[:SR*Visualize_Periods], label='Normal real')\n",
    "normal_pred, = plt.plot(y_normal[:SR*Visualize_Periods], label='Normal predicted')\n",
    "plt.legend(handles=[normal_real, normal_pred])\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(10,5))\n",
    "plt.grid(True)\n",
    "plt.title('Abormal data, Anomaly score: {}'.format(single_ab_loss.item()))\n",
    "plt.autoscale(axis='x', tight=True)\n",
    "abnormal_real, = plt.plot(test_ab_readings_labels.cpu().view(seq_lenth-1)[:SR*Visualize_Periods], label='Abnormal real')\n",
    "abnormal_pred, = plt.plot(y_abnormal[:SR*Visualize_Periods], label='Abnormal predicted')\n",
    "plt.legend(handles=[abnormal_real, abnormal_pred])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Show de-normalized predicted normal and abnormal time series data\n",
    "Orange line shows abnormal data while blue shows normal data. Both de-normalized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "normal_predictions = sine_wave.scaler.inverse_transform(y_normal.reshape(-1, 1)).flatten()\n",
    "abnormal_predictions = sine_wave.scaler.inverse_transform(y_abnormal.reshape(-1, 1)).flatten()\n",
    "plt.grid(True)\n",
    "plt.autoscale(axis='x', tight=True)\n",
    "plt.plot(normal_predictions.flatten()[0:100])\n",
    "plt.plot(abnormal_predictions.flatten()[0:100])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot normal prediction and target together to observe the difference\n",
    "For normal waveform, show the difference between predicted values and labels. Ideally they should be identical, but since waveform generator also generates some noise, they are not 100 percent identical. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(999,) (20, 1000)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('Current vs Time')\n",
    "plt.ylabel('Current (A)')\n",
    "plt.grid(True)\n",
    "plt.autoscale(axis='x', tight=True)\n",
    "print(normal_predictions.shape, sine_wave.disturbed_signal[:seq_lenth].shape)\n",
    "plt.plot(sine_wave.disturbed_signal[0, 1:41])\n",
    "plt.plot(normal_predictions.flatten()[0:40])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Free run this LSTM model with only predicted time series data points\n",
    "For sanity test, take only several datapoints at the beginning of a sine wave, and then append predicted values as next time series value, and repeat for 700 times. We would like to see if the model automatically generates something that resembles a sinewave."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1000])\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# model.eval()\n",
    "test_readings, test_abnormal_readings = sine_wave.re_generate_abnormal_single()\n",
    "print(test_readings.shape)\n",
    "\n",
    "# normal reading\n",
    "curr_segment = test_readings[0:6]\n",
    "for i in range(700):\n",
    "    curr_segment_processed = curr_segment.view(curr_segment.shape[0] ,1, 1)[i:curr_segment.shape[0], :, :]\n",
    "    single_pred = model(curr_segment_processed)[-1]\n",
    "    curr_segment = torch.cat((curr_segment, torch.flatten(single_pred)), 0)\n",
    "plt.figure(figsize=(10,5))\n",
    "plt.grid(True)\n",
    "plt.autoscale(axis='x', tight=True)\n",
    "normal_real, = plt.plot(curr_segment.cpu().detach().numpy(), label='estimated')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Save model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.save(model.state_dict(), './layer_1_batch50_lr0_01_hs50.pth')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Option 1: Load model in GPU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedDict([('lstm.weight_ih_l0',\n",
       "              tensor([[ 0.1448],\n",
       "                      [ 0.1378],\n",
       "                      [-0.1551],\n",
       "                      [-0.0255],\n",
       "                      [ 0.1019],\n",
       "                      [-0.0814],\n",
       "                      [ 0.0074],\n",
       "                      [-0.1563],\n",
       "                      [-0.1446],\n",
       "                      [ 0.0478],\n",
       "                      [-0.0181],\n",
       "                      [ 0.1081],\n",
       "                      [-0.0141],\n",
       "                      [-0.0802],\n",
       "                      [ 0.1208],\n",
       "                      [ 0.1193],\n",
       "                      [ 0.0704],\n",
       "                      [ 0.0727],\n",
       "                      [-0.0563],\n",
       "                      [ 0.1054],\n",
       "                      [-0.0587],\n",
       "                      [ 0.1481],\n",
       "                      [ 0.1008],\n",
       "                      [-0.1109],\n",
       "                      [ 0.1284],\n",
       "                      [ 0.0558],\n",
       "                      [-0.0374],\n",
       "                      [-0.0288],\n",
       "                      [-0.1089],\n",
       "                      [-0.0557],\n",
       "                      [-0.0988],\n",
       "                      [ 0.1182],\n",
       "                      [-0.0812],\n",
       "                      [-0.1221],\n",
       "                      [ 0.0111],\n",
       "                      [-0.0400],\n",
       "                      [-0.1201],\n",
       "                      [-0.1340],\n",
       "                      [-0.0455],\n",
       "                      [-0.0147],\n",
       "                      [ 0.0394],\n",
       "                      [ 0.0679],\n",
       "                      [-0.1150],\n",
       "                      [-0.0587],\n",
       "                      [-0.0315],\n",
       "                      [-0.0935],\n",
       "                      [ 0.1131],\n",
       "                      [ 0.1141],\n",
       "                      [ 0.0042],\n",
       "                      [ 0.1003],\n",
       "                      [ 0.0120],\n",
       "                      [-0.0164],\n",
       "                      [-0.0240],\n",
       "                      [-0.0283],\n",
       "                      [-0.0701],\n",
       "                      [ 0.0218],\n",
       "                      [ 0.0980],\n",
       "                      [ 0.0692],\n",
       "                      [-0.1468],\n",
       "                      [ 0.0535],\n",
       "                      [ 0.0169],\n",
       "                      [ 0.0488],\n",
       "                      [-0.1233],\n",
       "                      [ 0.1897],\n",
       "                      [ 0.0576],\n",
       "                      [-0.1238],\n",
       "                      [ 0.0734],\n",
       "                      [-0.0081],\n",
       "                      [-0.0844],\n",
       "                      [-0.0081],\n",
       "                      [ 0.1727],\n",
       "                      [ 0.1177],\n",
       "                      [ 0.0862],\n",
       "                      [ 0.1055],\n",
       "                      [ 0.0524],\n",
       "                      [ 0.0575],\n",
       "                      [-0.0623],\n",
       "                      [-0.0144],\n",
       "                      [-0.0751],\n",
       "                      [-0.0608],\n",
       "                      [ 0.1734],\n",
       "                      [-0.1358],\n",
       "                      [ 0.0960],\n",
       "                      [-0.0235],\n",
       "                      [-0.1000],\n",
       "                      [-0.0373],\n",
       "                      [ 0.0742],\n",
       "                      [-0.0318],\n",
       "                      [-0.1096],\n",
       "                      [ 0.1377],\n",
       "                      [-0.1861],\n",
       "                      [-0.0549],\n",
       "                      [ 0.0651],\n",
       "                      [-0.0829],\n",
       "                      [-0.0446],\n",
       "                      [ 0.0687],\n",
       "                      [-0.0186],\n",
       "                      [-0.1241],\n",
       "                      [ 0.0025],\n",
       "                      [ 0.0422],\n",
       "                      [ 0.3277],\n",
       "                      [-0.0471],\n",
       "                      [-0.1058],\n",
       "                      [ 0.4558],\n",
       "                      [ 0.2179],\n",
       "                      [ 0.3915],\n",
       "                      [-0.1855],\n",
       "                      [-0.4765],\n",
       "                      [ 0.3505],\n",
       "                      [-0.3330],\n",
       "                      [-0.3742],\n",
       "                      [-0.3244],\n",
       "                      [ 0.3584],\n",
       "                      [ 0.2341],\n",
       "                      [ 0.1947],\n",
       "                      [ 0.1840],\n",
       "                      [-0.2941],\n",
       "                      [ 0.1648],\n",
       "                      [ 0.0048],\n",
       "                      [ 0.4366],\n",
       "                      [-0.2641],\n",
       "                      [ 0.3609],\n",
       "                      [-0.3541],\n",
       "                      [ 0.4353],\n",
       "                      [ 0.0310],\n",
       "                      [ 0.0916],\n",
       "                      [ 0.0691],\n",
       "                      [-0.2504],\n",
       "                      [-0.2989],\n",
       "                      [-0.2692],\n",
       "                      [-0.1595],\n",
       "                      [ 0.2313],\n",
       "                      [ 0.6176],\n",
       "                      [-0.2612],\n",
       "                      [ 0.1029],\n",
       "                      [ 0.2733],\n",
       "                      [ 0.1430],\n",
       "                      [-0.3649],\n",
       "                      [ 0.1842],\n",
       "                      [-0.0910],\n",
       "                      [ 0.2449],\n",
       "                      [ 0.2993],\n",
       "                      [-0.4528],\n",
       "                      [-0.0329],\n",
       "                      [ 0.1315],\n",
       "                      [-0.4218],\n",
       "                      [ 0.2754],\n",
       "                      [ 0.2143],\n",
       "                      [ 0.1680],\n",
       "                      [-0.3136],\n",
       "                      [ 0.1793],\n",
       "                      [-0.0364],\n",
       "                      [-0.2132],\n",
       "                      [ 0.1162],\n",
       "                      [ 0.0968],\n",
       "                      [ 0.0114],\n",
       "                      [-0.0577],\n",
       "                      [-0.1652],\n",
       "                      [-0.0240],\n",
       "                      [-0.1251],\n",
       "                      [-0.1297],\n",
       "                      [ 0.0536],\n",
       "                      [-0.0123],\n",
       "                      [ 0.2191],\n",
       "                      [-0.1032],\n",
       "                      [-0.0607],\n",
       "                      [-0.0896],\n",
       "                      [-0.0951],\n",
       "                      [ 0.0932],\n",
       "                      [ 0.0600],\n",
       "                      [ 0.1387],\n",
       "                      [ 0.1979],\n",
       "                      [ 0.0317],\n",
       "                      [-0.0460],\n",
       "                      [-0.0423],\n",
       "                      [-0.1502],\n",
       "                      [-0.1013],\n",
       "                      [ 0.0421],\n",
       "                      [-0.1413],\n",
       "                      [-0.0175],\n",
       "                      [ 0.0482],\n",
       "                      [ 0.0509],\n",
       "                      [ 0.0913],\n",
       "                      [ 0.0089],\n",
       "                      [ 0.1102],\n",
       "                      [ 0.0112],\n",
       "                      [ 0.1064],\n",
       "                      [-0.1678],\n",
       "                      [ 0.0276],\n",
       "                      [-0.0521],\n",
       "                      [-0.1072],\n",
       "                      [ 0.0122],\n",
       "                      [-0.0774],\n",
       "                      [ 0.0908],\n",
       "                      [-0.0720],\n",
       "                      [ 0.0661],\n",
       "                      [ 0.0448],\n",
       "                      [ 0.0382],\n",
       "                      [-0.1218],\n",
       "                      [ 0.1740]], device='cuda:0')),\n",
       "             ('lstm.weight_hh_l0',\n",
       "              tensor([[ 0.0717,  0.0552, -0.0295,  ..., -0.1239, -0.1301, -0.1031],\n",
       "                      [ 0.0387,  0.1325, -0.0979,  ..., -0.0134, -0.0839,  0.0023],\n",
       "                      [-0.0548,  0.1037,  0.0878,  ..., -0.0663,  0.0878, -0.0131],\n",
       "                      ...,\n",
       "                      [-0.0450, -0.0119, -0.1345,  ...,  0.0206,  0.0130,  0.1126],\n",
       "                      [ 0.1111, -0.1075, -0.0525,  ...,  0.1362,  0.0281,  0.0031],\n",
       "                      [-0.0367, -0.0767,  0.1368,  ..., -0.0474,  0.0090, -0.0869]],\n",
       "                     device='cuda:0')),\n",
       "             ('lstm.bias_ih_l0',\n",
       "              tensor([ 0.0425, -0.1090,  0.0480,  0.2298,  0.0332,  0.1782,  0.1001,  0.1124,\n",
       "                       0.0041, -0.0277,  0.0297, -0.0126, -0.0857, -0.0225, -0.1080,  0.1070,\n",
       "                       0.0853,  0.0832, -0.0491,  0.1192, -0.0940,  0.1927,  0.1720, -0.0035,\n",
       "                      -0.1083,  0.1061,  0.0615, -0.0345,  0.0494, -0.0846, -0.0875, -0.0241,\n",
       "                       0.2854,  0.0873,  0.0631,  0.1532, -0.1125,  0.1383,  0.1426,  0.0944,\n",
       "                      -0.0335, -0.0125,  0.0104, -0.0425,  0.0496,  0.0591, -0.0667, -0.0014,\n",
       "                       0.0476,  0.0746,  0.0706, -0.1413, -0.1113, -0.0903,  0.0027, -0.1763,\n",
       "                       0.0244, -0.0368, -0.0186, -0.1391,  0.0056, -0.0964, -0.0733,  0.0552,\n",
       "                       0.0227, -0.0192,  0.1082,  0.0680,  0.0887, -0.1219, -0.1157, -0.1171,\n",
       "                      -0.1388, -0.1149, -0.1098, -0.1236, -0.0903,  0.0576,  0.0465, -0.0084,\n",
       "                       0.0644,  0.1203,  0.0050,  0.0388, -0.0411,  0.1117, -0.0225, -0.0007,\n",
       "                       0.1030,  0.0919, -0.1397, -0.0262,  0.0773,  0.0583,  0.0491, -0.0114,\n",
       "                      -0.0835, -0.1012, -0.0200, -0.1531,  0.0229,  0.1259, -0.1440,  0.3023,\n",
       "                       0.0572,  0.0923,  0.0442, -0.0648, -0.1794,  0.1328, -0.1222,  0.0748,\n",
       "                      -0.0957,  0.2157, -0.0907, -0.0639, -0.0728, -0.2132, -0.2150, -0.0855,\n",
       "                      -0.1165, -0.1602, -0.1582,  0.1650, -0.0091, -0.0911, -0.1794,  0.0662,\n",
       "                       0.0299,  0.0563,  0.1423,  0.2017,  0.2172, -0.0125, -0.1476, -0.1166,\n",
       "                      -0.0455,  0.0469, -0.0175,  0.1318, -0.2102,  0.0574, -0.0723,  0.0166,\n",
       "                      -0.0708, -0.0427,  0.0151,  0.0419,  0.0810, -0.0860,  0.0324, -0.0436,\n",
       "                       0.0671,  0.1973, -0.0060, -0.0313,  0.0125,  0.0366,  0.1199,  0.0435,\n",
       "                      -0.0099, -0.0135,  0.0395,  0.0622, -0.1174,  0.0807,  0.0698,  0.1313,\n",
       "                       0.1001,  0.0812, -0.0831,  0.0076,  0.1149,  0.0707, -0.0923,  0.1252,\n",
       "                       0.0600,  0.1515,  0.1614, -0.1135, -0.0358,  0.1734,  0.2755, -0.1163,\n",
       "                      -0.0145, -0.1134, -0.0867, -0.0075,  0.0387,  0.0945,  0.0890,  0.0378,\n",
       "                       0.0670, -0.0160, -0.0894,  0.0838, -0.0093, -0.0659, -0.0359,  0.0561],\n",
       "                     device='cuda:0')),\n",
       "             ('lstm.bias_hh_l0',\n",
       "              tensor([-0.0736,  0.0712,  0.1211,  0.2524, -0.1008,  0.0929, -0.0164,  0.2602,\n",
       "                      -0.0489,  0.0141, -0.0754,  0.0687,  0.0109,  0.0397, -0.0511, -0.0663,\n",
       "                       0.1352,  0.0099, -0.0537,  0.1853, -0.0496,  0.0857,  0.1796, -0.0119,\n",
       "                      -0.1265, -0.0443,  0.0943, -0.0343,  0.0588, -0.1072,  0.0558,  0.1208,\n",
       "                       0.2967,  0.0499,  0.0298,  0.0267, -0.0054,  0.2017, -0.0129,  0.0827,\n",
       "                       0.2014, -0.0534,  0.0108, -0.0813, -0.0478,  0.0530,  0.0918, -0.0330,\n",
       "                      -0.0736,  0.0593,  0.0565,  0.0495, -0.0447, -0.1273,  0.0351, -0.0788,\n",
       "                      -0.0057, -0.2181,  0.0149,  0.0663, -0.0579,  0.0693, -0.0108,  0.0869,\n",
       "                      -0.1157, -0.0357, -0.0130,  0.0679,  0.0323, -0.0355, -0.0520, -0.0215,\n",
       "                       0.0975,  0.0630,  0.0145,  0.0623,  0.0812, -0.1215, -0.0115, -0.1149,\n",
       "                       0.0497,  0.0547, -0.1810, -0.0911, -0.1028,  0.0695,  0.0252,  0.0304,\n",
       "                       0.0177,  0.0277, -0.0272,  0.1184,  0.0386, -0.0650, -0.0617, -0.0011,\n",
       "                      -0.0760, -0.1363,  0.0913,  0.0382,  0.1058, -0.1196, -0.1583,  0.2875,\n",
       "                       0.0099,  0.0180, -0.1260, -0.0798, -0.1689,  0.1348, -0.1034, -0.1240,\n",
       "                       0.0356,  0.2273, -0.0634, -0.0982,  0.0159,  0.0292, -0.2148,  0.0440,\n",
       "                      -0.0904, -0.2835,  0.0032,  0.0455,  0.0696, -0.0460, -0.0288, -0.0041,\n",
       "                      -0.0461,  0.0206,  0.1886,  0.2758,  0.0551,  0.0848,  0.0958, -0.1031,\n",
       "                       0.0386, -0.0097,  0.1740,  0.0637,  0.0321, -0.1217, -0.1159, -0.1832,\n",
       "                       0.0215, -0.0891,  0.1206,  0.0667,  0.1011, -0.0407, -0.0507, -0.1326,\n",
       "                       0.0607,  0.1296,  0.0021,  0.0694, -0.0414,  0.2469, -0.0278, -0.0533,\n",
       "                       0.1744,  0.0050,  0.0792,  0.0052,  0.0154, -0.0129,  0.0623,  0.1569,\n",
       "                       0.0204,  0.1461,  0.0989,  0.1710,  0.1251,  0.1512,  0.0858,  0.1032,\n",
       "                      -0.1212,  0.1001,  0.1442,  0.1101, -0.0348,  0.1603,  0.2581, -0.0956,\n",
       "                      -0.1129,  0.0059, -0.0784,  0.1706,  0.0820, -0.0039,  0.1732,  0.0357,\n",
       "                       0.1011,  0.0273,  0.0698,  0.2253,  0.0680,  0.0269, -0.1147, -0.0292],\n",
       "                     device='cuda:0')),\n",
       "             ('linear.weight',\n",
       "              tensor([[ 0.4355, -0.0830,  0.2740,  0.4930,  0.1320,  0.4314,  0.0017, -0.6699,\n",
       "                        0.2118, -0.1868, -0.2148, -0.3001,  0.2295,  0.4851,  0.1639,  0.3787,\n",
       "                       -0.1957,  0.6135, -0.1145,  0.4821, -0.2711, -0.1649, -0.3755,  0.3211,\n",
       "                       -0.0386,  0.1118,  0.1022, -0.1826, -0.5282, -0.0665,  0.0913, -0.0869,\n",
       "                        1.0626, -0.1839,  0.0891,  0.1290,  0.0015, -0.6798, -0.0473,  0.3217,\n",
       "                        0.5545,  0.2288, -0.3950, -0.0281,  0.0354, -0.4795,  0.3577,  0.2711,\n",
       "                        0.0645, -0.2162]], device='cuda:0')),\n",
       "             ('linear.bias', tensor([-0.3116], device='cuda:0'))])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = LSTM()\n",
    "with open('model.pth', 'rb') as f:\n",
    "    model.load_state_dict(torch.load(f, map_location=torch.device('cuda')))\n",
    "model.to('cuda').state_dict()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Option 2: Load model in CPU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedDict([('lstm.weight_ih_l0',\n",
       "              tensor([[ 0.1448],\n",
       "                      [ 0.1378],\n",
       "                      [-0.1551],\n",
       "                      [-0.0255],\n",
       "                      [ 0.1019],\n",
       "                      [-0.0814],\n",
       "                      [ 0.0074],\n",
       "                      [-0.1563],\n",
       "                      [-0.1446],\n",
       "                      [ 0.0478],\n",
       "                      [-0.0181],\n",
       "                      [ 0.1081],\n",
       "                      [-0.0141],\n",
       "                      [-0.0802],\n",
       "                      [ 0.1208],\n",
       "                      [ 0.1193],\n",
       "                      [ 0.0704],\n",
       "                      [ 0.0727],\n",
       "                      [-0.0563],\n",
       "                      [ 0.1054],\n",
       "                      [-0.0587],\n",
       "                      [ 0.1481],\n",
       "                      [ 0.1008],\n",
       "                      [-0.1109],\n",
       "                      [ 0.1284],\n",
       "                      [ 0.0558],\n",
       "                      [-0.0374],\n",
       "                      [-0.0288],\n",
       "                      [-0.1089],\n",
       "                      [-0.0557],\n",
       "                      [-0.0988],\n",
       "                      [ 0.1182],\n",
       "                      [-0.0812],\n",
       "                      [-0.1221],\n",
       "                      [ 0.0111],\n",
       "                      [-0.0400],\n",
       "                      [-0.1201],\n",
       "                      [-0.1340],\n",
       "                      [-0.0455],\n",
       "                      [-0.0147],\n",
       "                      [ 0.0394],\n",
       "                      [ 0.0679],\n",
       "                      [-0.1150],\n",
       "                      [-0.0587],\n",
       "                      [-0.0315],\n",
       "                      [-0.0935],\n",
       "                      [ 0.1131],\n",
       "                      [ 0.1141],\n",
       "                      [ 0.0042],\n",
       "                      [ 0.1003],\n",
       "                      [ 0.0120],\n",
       "                      [-0.0164],\n",
       "                      [-0.0240],\n",
       "                      [-0.0283],\n",
       "                      [-0.0701],\n",
       "                      [ 0.0218],\n",
       "                      [ 0.0980],\n",
       "                      [ 0.0692],\n",
       "                      [-0.1468],\n",
       "                      [ 0.0535],\n",
       "                      [ 0.0169],\n",
       "                      [ 0.0488],\n",
       "                      [-0.1233],\n",
       "                      [ 0.1897],\n",
       "                      [ 0.0576],\n",
       "                      [-0.1238],\n",
       "                      [ 0.0734],\n",
       "                      [-0.0081],\n",
       "                      [-0.0844],\n",
       "                      [-0.0081],\n",
       "                      [ 0.1727],\n",
       "                      [ 0.1177],\n",
       "                      [ 0.0862],\n",
       "                      [ 0.1055],\n",
       "                      [ 0.0524],\n",
       "                      [ 0.0575],\n",
       "                      [-0.0623],\n",
       "                      [-0.0144],\n",
       "                      [-0.0751],\n",
       "                      [-0.0608],\n",
       "                      [ 0.1734],\n",
       "                      [-0.1358],\n",
       "                      [ 0.0960],\n",
       "                      [-0.0235],\n",
       "                      [-0.1000],\n",
       "                      [-0.0373],\n",
       "                      [ 0.0742],\n",
       "                      [-0.0318],\n",
       "                      [-0.1096],\n",
       "                      [ 0.1377],\n",
       "                      [-0.1861],\n",
       "                      [-0.0549],\n",
       "                      [ 0.0651],\n",
       "                      [-0.0829],\n",
       "                      [-0.0446],\n",
       "                      [ 0.0687],\n",
       "                      [-0.0186],\n",
       "                      [-0.1241],\n",
       "                      [ 0.0025],\n",
       "                      [ 0.0422],\n",
       "                      [ 0.3277],\n",
       "                      [-0.0471],\n",
       "                      [-0.1058],\n",
       "                      [ 0.4558],\n",
       "                      [ 0.2179],\n",
       "                      [ 0.3915],\n",
       "                      [-0.1855],\n",
       "                      [-0.4765],\n",
       "                      [ 0.3505],\n",
       "                      [-0.3330],\n",
       "                      [-0.3742],\n",
       "                      [-0.3244],\n",
       "                      [ 0.3584],\n",
       "                      [ 0.2341],\n",
       "                      [ 0.1947],\n",
       "                      [ 0.1840],\n",
       "                      [-0.2941],\n",
       "                      [ 0.1648],\n",
       "                      [ 0.0048],\n",
       "                      [ 0.4366],\n",
       "                      [-0.2641],\n",
       "                      [ 0.3609],\n",
       "                      [-0.3541],\n",
       "                      [ 0.4353],\n",
       "                      [ 0.0310],\n",
       "                      [ 0.0916],\n",
       "                      [ 0.0691],\n",
       "                      [-0.2504],\n",
       "                      [-0.2989],\n",
       "                      [-0.2692],\n",
       "                      [-0.1595],\n",
       "                      [ 0.2313],\n",
       "                      [ 0.6176],\n",
       "                      [-0.2612],\n",
       "                      [ 0.1029],\n",
       "                      [ 0.2733],\n",
       "                      [ 0.1430],\n",
       "                      [-0.3649],\n",
       "                      [ 0.1842],\n",
       "                      [-0.0910],\n",
       "                      [ 0.2449],\n",
       "                      [ 0.2993],\n",
       "                      [-0.4528],\n",
       "                      [-0.0329],\n",
       "                      [ 0.1315],\n",
       "                      [-0.4218],\n",
       "                      [ 0.2754],\n",
       "                      [ 0.2143],\n",
       "                      [ 0.1680],\n",
       "                      [-0.3136],\n",
       "                      [ 0.1793],\n",
       "                      [-0.0364],\n",
       "                      [-0.2132],\n",
       "                      [ 0.1162],\n",
       "                      [ 0.0968],\n",
       "                      [ 0.0114],\n",
       "                      [-0.0577],\n",
       "                      [-0.1652],\n",
       "                      [-0.0240],\n",
       "                      [-0.1251],\n",
       "                      [-0.1297],\n",
       "                      [ 0.0536],\n",
       "                      [-0.0123],\n",
       "                      [ 0.2191],\n",
       "                      [-0.1032],\n",
       "                      [-0.0607],\n",
       "                      [-0.0896],\n",
       "                      [-0.0951],\n",
       "                      [ 0.0932],\n",
       "                      [ 0.0600],\n",
       "                      [ 0.1387],\n",
       "                      [ 0.1979],\n",
       "                      [ 0.0317],\n",
       "                      [-0.0460],\n",
       "                      [-0.0423],\n",
       "                      [-0.1502],\n",
       "                      [-0.1013],\n",
       "                      [ 0.0421],\n",
       "                      [-0.1413],\n",
       "                      [-0.0175],\n",
       "                      [ 0.0482],\n",
       "                      [ 0.0509],\n",
       "                      [ 0.0913],\n",
       "                      [ 0.0089],\n",
       "                      [ 0.1102],\n",
       "                      [ 0.0112],\n",
       "                      [ 0.1064],\n",
       "                      [-0.1678],\n",
       "                      [ 0.0276],\n",
       "                      [-0.0521],\n",
       "                      [-0.1072],\n",
       "                      [ 0.0122],\n",
       "                      [-0.0774],\n",
       "                      [ 0.0908],\n",
       "                      [-0.0720],\n",
       "                      [ 0.0661],\n",
       "                      [ 0.0448],\n",
       "                      [ 0.0382],\n",
       "                      [-0.1218],\n",
       "                      [ 0.1740]])),\n",
       "             ('lstm.weight_hh_l0',\n",
       "              tensor([[ 0.0717,  0.0552, -0.0295,  ..., -0.1239, -0.1301, -0.1031],\n",
       "                      [ 0.0387,  0.1325, -0.0979,  ..., -0.0134, -0.0839,  0.0023],\n",
       "                      [-0.0548,  0.1037,  0.0878,  ..., -0.0663,  0.0878, -0.0131],\n",
       "                      ...,\n",
       "                      [-0.0450, -0.0119, -0.1345,  ...,  0.0206,  0.0130,  0.1126],\n",
       "                      [ 0.1111, -0.1075, -0.0525,  ...,  0.1362,  0.0281,  0.0031],\n",
       "                      [-0.0367, -0.0767,  0.1368,  ..., -0.0474,  0.0090, -0.0869]])),\n",
       "             ('lstm.bias_ih_l0',\n",
       "              tensor([ 0.0425, -0.1090,  0.0480,  0.2298,  0.0332,  0.1782,  0.1001,  0.1124,\n",
       "                       0.0041, -0.0277,  0.0297, -0.0126, -0.0857, -0.0225, -0.1080,  0.1070,\n",
       "                       0.0853,  0.0832, -0.0491,  0.1192, -0.0940,  0.1927,  0.1720, -0.0035,\n",
       "                      -0.1083,  0.1061,  0.0615, -0.0345,  0.0494, -0.0846, -0.0875, -0.0241,\n",
       "                       0.2854,  0.0873,  0.0631,  0.1532, -0.1125,  0.1383,  0.1426,  0.0944,\n",
       "                      -0.0335, -0.0125,  0.0104, -0.0425,  0.0496,  0.0591, -0.0667, -0.0014,\n",
       "                       0.0476,  0.0746,  0.0706, -0.1413, -0.1113, -0.0903,  0.0027, -0.1763,\n",
       "                       0.0244, -0.0368, -0.0186, -0.1391,  0.0056, -0.0964, -0.0733,  0.0552,\n",
       "                       0.0227, -0.0192,  0.1082,  0.0680,  0.0887, -0.1219, -0.1157, -0.1171,\n",
       "                      -0.1388, -0.1149, -0.1098, -0.1236, -0.0903,  0.0576,  0.0465, -0.0084,\n",
       "                       0.0644,  0.1203,  0.0050,  0.0388, -0.0411,  0.1117, -0.0225, -0.0007,\n",
       "                       0.1030,  0.0919, -0.1397, -0.0262,  0.0773,  0.0583,  0.0491, -0.0114,\n",
       "                      -0.0835, -0.1012, -0.0200, -0.1531,  0.0229,  0.1259, -0.1440,  0.3023,\n",
       "                       0.0572,  0.0923,  0.0442, -0.0648, -0.1794,  0.1328, -0.1222,  0.0748,\n",
       "                      -0.0957,  0.2157, -0.0907, -0.0639, -0.0728, -0.2132, -0.2150, -0.0855,\n",
       "                      -0.1165, -0.1602, -0.1582,  0.1650, -0.0091, -0.0911, -0.1794,  0.0662,\n",
       "                       0.0299,  0.0563,  0.1423,  0.2017,  0.2172, -0.0125, -0.1476, -0.1166,\n",
       "                      -0.0455,  0.0469, -0.0175,  0.1318, -0.2102,  0.0574, -0.0723,  0.0166,\n",
       "                      -0.0708, -0.0427,  0.0151,  0.0419,  0.0810, -0.0860,  0.0324, -0.0436,\n",
       "                       0.0671,  0.1973, -0.0060, -0.0313,  0.0125,  0.0366,  0.1199,  0.0435,\n",
       "                      -0.0099, -0.0135,  0.0395,  0.0622, -0.1174,  0.0807,  0.0698,  0.1313,\n",
       "                       0.1001,  0.0812, -0.0831,  0.0076,  0.1149,  0.0707, -0.0923,  0.1252,\n",
       "                       0.0600,  0.1515,  0.1614, -0.1135, -0.0358,  0.1734,  0.2755, -0.1163,\n",
       "                      -0.0145, -0.1134, -0.0867, -0.0075,  0.0387,  0.0945,  0.0890,  0.0378,\n",
       "                       0.0670, -0.0160, -0.0894,  0.0838, -0.0093, -0.0659, -0.0359,  0.0561])),\n",
       "             ('lstm.bias_hh_l0',\n",
       "              tensor([-0.0736,  0.0712,  0.1211,  0.2524, -0.1008,  0.0929, -0.0164,  0.2602,\n",
       "                      -0.0489,  0.0141, -0.0754,  0.0687,  0.0109,  0.0397, -0.0511, -0.0663,\n",
       "                       0.1352,  0.0099, -0.0537,  0.1853, -0.0496,  0.0857,  0.1796, -0.0119,\n",
       "                      -0.1265, -0.0443,  0.0943, -0.0343,  0.0588, -0.1072,  0.0558,  0.1208,\n",
       "                       0.2967,  0.0499,  0.0298,  0.0267, -0.0054,  0.2017, -0.0129,  0.0827,\n",
       "                       0.2014, -0.0534,  0.0108, -0.0813, -0.0478,  0.0530,  0.0918, -0.0330,\n",
       "                      -0.0736,  0.0593,  0.0565,  0.0495, -0.0447, -0.1273,  0.0351, -0.0788,\n",
       "                      -0.0057, -0.2181,  0.0149,  0.0663, -0.0579,  0.0693, -0.0108,  0.0869,\n",
       "                      -0.1157, -0.0357, -0.0130,  0.0679,  0.0323, -0.0355, -0.0520, -0.0215,\n",
       "                       0.0975,  0.0630,  0.0145,  0.0623,  0.0812, -0.1215, -0.0115, -0.1149,\n",
       "                       0.0497,  0.0547, -0.1810, -0.0911, -0.1028,  0.0695,  0.0252,  0.0304,\n",
       "                       0.0177,  0.0277, -0.0272,  0.1184,  0.0386, -0.0650, -0.0617, -0.0011,\n",
       "                      -0.0760, -0.1363,  0.0913,  0.0382,  0.1058, -0.1196, -0.1583,  0.2875,\n",
       "                       0.0099,  0.0180, -0.1260, -0.0798, -0.1689,  0.1348, -0.1034, -0.1240,\n",
       "                       0.0356,  0.2273, -0.0634, -0.0982,  0.0159,  0.0292, -0.2148,  0.0440,\n",
       "                      -0.0904, -0.2835,  0.0032,  0.0455,  0.0696, -0.0460, -0.0288, -0.0041,\n",
       "                      -0.0461,  0.0206,  0.1886,  0.2758,  0.0551,  0.0848,  0.0958, -0.1031,\n",
       "                       0.0386, -0.0097,  0.1740,  0.0637,  0.0321, -0.1217, -0.1159, -0.1832,\n",
       "                       0.0215, -0.0891,  0.1206,  0.0667,  0.1011, -0.0407, -0.0507, -0.1326,\n",
       "                       0.0607,  0.1296,  0.0021,  0.0694, -0.0414,  0.2469, -0.0278, -0.0533,\n",
       "                       0.1744,  0.0050,  0.0792,  0.0052,  0.0154, -0.0129,  0.0623,  0.1569,\n",
       "                       0.0204,  0.1461,  0.0989,  0.1710,  0.1251,  0.1512,  0.0858,  0.1032,\n",
       "                      -0.1212,  0.1001,  0.1442,  0.1101, -0.0348,  0.1603,  0.2581, -0.0956,\n",
       "                      -0.1129,  0.0059, -0.0784,  0.1706,  0.0820, -0.0039,  0.1732,  0.0357,\n",
       "                       0.1011,  0.0273,  0.0698,  0.2253,  0.0680,  0.0269, -0.1147, -0.0292])),\n",
       "             ('linear.weight',\n",
       "              tensor([[ 0.4355, -0.0830,  0.2740,  0.4930,  0.1320,  0.4314,  0.0017, -0.6699,\n",
       "                        0.2118, -0.1868, -0.2148, -0.3001,  0.2295,  0.4851,  0.1639,  0.3787,\n",
       "                       -0.1957,  0.6135, -0.1145,  0.4821, -0.2711, -0.1649, -0.3755,  0.3211,\n",
       "                       -0.0386,  0.1118,  0.1022, -0.1826, -0.5282, -0.0665,  0.0913, -0.0869,\n",
       "                        1.0626, -0.1839,  0.0891,  0.1290,  0.0015, -0.6798, -0.0473,  0.3217,\n",
       "                        0.5545,  0.2288, -0.3950, -0.0281,  0.0354, -0.4795,  0.3577,  0.2711,\n",
       "                        0.0645, -0.2162]])),\n",
       "             ('linear.bias', tensor([-0.3116]))])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = LSTM()\n",
    "with open('model.pth', 'rb') as f:\n",
    "    model.load_state_dict(torch.load(f, map_location=torch.device('cpu')))\n",
    "model.to('cpu').state_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "conda_pytorch_latest_p36",
   "language": "python",
   "name": "conda_pytorch_latest_p36"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}