{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "\"\"\" use smaller learning rate for gradient descent or increase batch size \"\"\"\n",
    "\n",
    "import os \n",
    "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' \n",
    "import time \n",
    "import numpy as np\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "import tensorflow as tf\n",
    "tf.compat.v1.disable_eager_execution() \n",
    "import tensorflow_probability as tfp\n",
    "import tensorflow.python.util.deprecation as deprecation\n",
    "deprecation._PRINT_DEPRECATION_WARNINGS = False\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from data_loader import load_data\n",
    "from data_preprocesser import preprocess_data\n",
    "from maf import MAF \n",
    "from experiment import Experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data successfully loaded...\n",
      "\n",
      "Data successfully preprocessed...\n",
      "\n",
      "TensorFlow version: 2.5.0\n",
      "Number of dimensions: 37\n",
      "Learning rate: 0.0001\n",
      "\n",
      "Successfully created model...\n",
      "\n",
      "Optimizer: Adam_2\n",
      "Optimizer and loss successfully defined...\n",
      "\n",
      "Iteration 0: 52.72296142578125\n",
      "Iteration 10000: -12.123727798461914\n",
      "Iteration 20000: -31.257366180419922\n",
      "Iteration 30000: -19.52370834350586\n",
      "Iteration 40000: -34.72262954711914\n",
      "Iteration 50000: -37.22956085205078\n",
      "Iteration 60000: -31.837202072143555\n",
      "Iteration 70000: -36.162353515625\n",
      "Iteration 80000: -40.44646453857422\n",
      "Iteration 90000: -39.50082015991211\n",
      "\n",
      "Training completed...\n",
      "Training time: 508.4956090450287 seconds\n",
      "Training finished...\n",
      "\n",
      "Displaying results...\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizer: RMSProp\n",
      "Optimizer and loss successfully defined...\n",
      "\n",
      "Iteration 0: 52.72296142578125\n",
      "Iteration 10000: -8.40821361541748\n",
      "Iteration 20000: -24.88846778869629\n",
      "Iteration 30000: -13.85255241394043\n",
      "Iteration 40000: -30.42304229736328\n",
      "Iteration 50000: -33.980743408203125\n",
      "Iteration 60000: -26.754453659057617\n",
      "Iteration 70000: -35.094207763671875\n",
      "Iteration 80000: -34.587615966796875\n",
      "Iteration 90000: -27.752574920654297\n",
      "\n",
      "Training completed...\n",
      "Training time: 565.5382442474365 seconds\n",
      "Training finished...\n",
      "\n",
      "Displaying results...\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizer: GradientDescent\n",
      "Optimizer and loss successfully defined...\n",
      "\n",
      "Iteration 0: 52.72296142578125\n",
      "Iteration 10000: 31.858509063720703\n",
      "Iteration 20000: 14.227487564086914\n",
      "Iteration 30000: 5.67965841293335\n",
      "Iteration 40000: -4.409252643585205\n",
      "Iteration 50000: nan\n",
      "Iteration 60000: nan\n",
      "Iteration 70000: nan\n",
      "Iteration 80000: nan\n",
      "Iteration 90000: nan\n",
      "\n",
      "Training completed...\n",
      "Training time: 490.9801027774811 seconds\n",
      "Training finished...\n",
      "\n",
      "Displaying results...\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def train(session, loss, optimizer, steps=int(1e5)):\n",
    "    \n",
    "    \"\"\" optimize for all dimensions \"\"\"\n",
    "    \n",
    "    start_time = time.time()\n",
    "    \n",
    "    recorded_steps = []\n",
    "    recorded_losses = []\n",
    "    for i in range(steps):\n",
    "        _, loss_per_iteration = session.run([optimizer, loss])\n",
    "        if i % 100 == 0:\n",
    "            recorded_steps.append(i)\n",
    "            recorded_losses.append(loss_per_iteration)\n",
    "        if i % int(1e4) == 0:\n",
    "            print('Iteration {iteration}: {loss}'.format(iteration=i,loss=loss_per_iteration))\n",
    "    print('\\nTraining completed...')\n",
    "    print(f'Training time: {time.time() - start_time} seconds')\n",
    "    return recorded_losses\n",
    "\n",
    "\n",
    "def plot_results(recorded_losses):\n",
    "    \n",
    "    \"\"\" plot loss \"\"\"\n",
    "    print('Displaying results...')\n",
    "    fig = plt.figure(figsize=(10,5))\n",
    "    x = np.arange(len(recorded_losses))\n",
    "    y = recorded_losses\n",
    "    m, b = np.polyfit(x, y, 1) \n",
    "    plt.scatter(x, y, s=10, alpha=0.3)\n",
    "    plt.plot(x, m*x+b, c=\"r\")\n",
    "    plt.title('Loss per 100 iteration')\n",
    "    plt.xlabel('Iteration')\n",
    "    plt.ylabel('Loss')\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "def main():\n",
    "    \n",
    "    \"\"\" load data \"\"\"\n",
    "\n",
    "    filename = 'prostate.xls'\n",
    "    directory = '/Users/kaanguney.keklikci/Data/'\n",
    "\n",
    "    loader = load_data(filename, directory)\n",
    "    loader.create_directory(directory)\n",
    "    data = loader.read_data(directory, filename)\n",
    "    print('Data successfully loaded...\\n')\n",
    "    \n",
    "    \"\"\" preprocess data \"\"\"\n",
    "\n",
    "    fillna_vals = ['sz', 'sg', 'wt']\n",
    "    dropna_vals = ['ekg', 'age']\n",
    "    drop_vals = ['patno', 'sdate']\n",
    "\n",
    "    preprocesser = preprocess_data(StandardScaler(), fillna_vals, dropna_vals, drop_vals)\n",
    "    data = preprocesser.dropna_features(data)\n",
    "    data = preprocesser.impute(data)\n",
    "    data = preprocesser.drop_features(data)\n",
    "    data = preprocesser.encode_categorical(data)\n",
    "    data = preprocesser.scale(data)\n",
    "    print('Data successfully preprocessed...\\n')\n",
    "    \n",
    "    \"\"\" set MAF parameters \"\"\"\n",
    "\n",
    "    batch_size = 32\n",
    "    dtype = np.float32\n",
    "    tf_version = tf.__version__\n",
    "    params = 2\n",
    "    hidden_units = [512,512]\n",
    "    base_dist = tfp.distributions.Normal(loc=0., scale=1., name=\"gaussian\")\n",
    "    dims = data.shape[1]\n",
    "    learning_rate = 1e-4\n",
    "    steps = 1e4\n",
    "\n",
    "    \"\"\" initialize samples \"\"\"\n",
    "\n",
    "    maf = MAF(dtype, tf_version, batch_size, params, hidden_units, base_dist, dims)\n",
    "\n",
    "    dims = maf.get_dims(data)\n",
    "    samples = maf.create_tensor(data)\n",
    "    print(f'TensorFlow version: {maf.tf_version}')\n",
    "    print(f'Number of dimensions: {maf.dims}')\n",
    "    print(f'Learning rate: {learning_rate}\\n')\n",
    "    \n",
    "    \"\"\" initialize MAF \"\"\"\n",
    "\n",
    "    maf = maf.make_maf(data)\n",
    "    print('Successfully created model...\\n')\n",
    "    \n",
    "    \"\"\" initialize loss and optimizer \"\"\"\n",
    "\n",
    "    loss = -tf.reduce_mean(maf.log_prob(samples))\n",
    "    optimizer = tf.compat.v1.train.AdamOptimizer(learning_rate).minimize(loss)\n",
    "    \n",
    "    experiment = Experiment(optimizer, learning_rate, loss, steps)\n",
    "    \n",
    "    keywords = ['adam', 'rmsprop', 'sgd']\n",
    "    \n",
    "    for keyword in keywords:\n",
    "    \n",
    "        session = tf.compat.v1.Session()\n",
    "        tf.compat.v1.set_random_seed(42)\n",
    "        experiment.change_optimizer(learning_rate, loss, keyword=keyword)\n",
    "        optimizer = experiment.get_optimizer()\n",
    "        session.run(tf.compat.v1.global_variables_initializer())\n",
    "        print(f'Optimizer: {optimizer.name}')\n",
    "        print('Optimizer and loss successfully defined...\\n')\n",
    "\n",
    "        \"\"\" start training \"\"\"\n",
    "        recorded_losses = train(session, loss, optimizer)\n",
    "        print('Training finished...\\n')\n",
    "\n",
    "        \"\"\" display results \"\"\"\n",
    "        plot_results(recorded_losses)\n",
    "    \n",
    "    \n",
    "if __name__ == \"__main__\":\n",
    "    main()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}