single_site_field_update.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e7e2e9e3-0e1f-4bab-816f-e838e1f5b9e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#from __future__ import absolute_import, division, print_function, unicode_literals\n",
    "#from realistic_python_call import ffi\n",
    "import numpy as np\n",
    "import sys\n",
    "#sys.argv = ['pdm']\n",
    "import tensorflow as tf\n",
    "\n",
    "from tensorflow.python import keras\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "class MyFcClass:\n",
    "    def __init__(self):\n",
    "        print (\"hello in constructor of MyFcClass\")\n",
    "        self.Ntrain = 130000\n",
    "        self.Nvalid = 20000\n",
    "        self.size = 28\n",
    "        self.nclass = 1\n",
    "        self.h1 = 15\n",
    "        self.h2 = 10\n",
    "        self.batch_size = 1000\n",
    "        self.epochs = 200\n",
    "        print (\"num epoch: \",self.epochs)\n",
    "        self.display_freq = 1\n",
    "        self.learning_rate = 0.0025\n",
    "        self.x_train = np.zeros((self.Ntrain,self.size),dtype = 'float')\n",
    "        self.y_train = np.zeros((self.Ntrain,self.nclass),dtype = 'float')\n",
    "        self.x_valid = np.zeros((self.Nvalid,self.size),dtype = 'float')\n",
    "        self.y_valid = np.zeros((self.Nvalid,self.nclass),dtype = 'float')\n",
    "    \n",
    "        self.output = self.create_model() \n",
    "    \n",
    "        self.loss = 'logcosh' # 'mean_squared_error'\n",
    "\n",
    "        self.optim = tf.keras.optimizers.Adam(lr=self.learning_rate, beta_1=0.9, beta_2=0.999, epsilon=None, decay=0.0, amsgrad=False)\n",
    "        \n",
    "    def create_model(self):\n",
    "        model = tf.keras.Sequential()\n",
    "        model.add(tf.keras.layers.Dense(20, activation='softplus'))\n",
    "        model.add(tf.keras.layers.Dense(1, activation='linear'))\n",
    "        \n",
    "        return model\n",
    "   \n",
    "    def load_data(self):\n",
    "        print('now loading data')\n",
    "        data_dqmc = np.loadtxt(\"DataSingleOut_short.txt\", usecols = range(0,33))\n",
    "        self.x_train = data_dqmc[0:self.Ntrain,4:32]\n",
    "        self.y_train = data_dqmc[0:self.Ntrain,2:3]\n",
    "\n",
    "        self.x_valid = data_dqmc[self.Ntrain:self.Ntrain+self.Nvalid,4:32]\n",
    "        self.y_valid = data_dqmc[self.Ntrain:self.Ntrain+self.Nvalid,2:3]\n",
    "\n",
    "\n",
    "        print('x_train:\\t{}'.format(self.x_train.shape))\n",
    "        print('y_train:\\t{}'.format(self.y_train.shape))\n",
    "        print('x_valid:\\t{}'.format(self.x_valid.shape))\n",
    "        print('y_valid:\\t{}'.format(self.y_valid.shape))\n",
    "    \n",
    "    def reshape_data(self):\n",
    "        w, h = self.size, 1\n",
    "        self.x_train = self.x_train.reshape(self.x_train.shape[0], w, h, 1)\n",
    "        self.x_test = self.x_test.reshape(self.x_test.shape[0], w, h, 1)\n",
    "        \n",
    "    def save_model(self):\n",
    "        self.output.save('fcmodel.h5')\n",
    "      \n",
    "    def restore_model(self):\n",
    "        self.output = tf.keras.models.load_model('fcmodel.h5')  \n",
    "        \n",
    "    def train_now(self):\n",
    "        print('compiling now')\n",
    "        self.output.compile(loss=self.loss,\n",
    "                 optimizer=self.optim,\n",
    "                 metrics=['accuracy'])\n",
    "        print('training now')\n",
    "        self.output.fit(self.x_train,\n",
    "             self.y_train,\n",
    "            batch_size=self.batch_size,\n",
    "            epochs=self.epochs)    \n",
    "        \n",
    "        \n",
    "    def predict_now(self):\n",
    "        p = self.output.predict(self.x_valid)\n",
    "        plt.plot(p,self.y_valid,'o')\n",
    "        plt.show()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "34e19802-3070-4f63-9823-1cd872cb548c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello in constructor of MyFcClass\n",
      "num epoch:  200\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.9/site-packages/keras/optimizer_v2/adam.py:105: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.\n",
      "  super(Adam, self).__init__(name, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "if __name__ == \"__main__\":\n",
    "\n",
    "    my_obj = MyFcClass()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "930181e6-f152-4c42-b319-9102ce8c7e17",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now loading data\n",
      "x_train:\t(130000, 28)\n",
      "y_train:\t(130000, 1)\n",
      "x_valid:\t(20000, 28)\n",
      "y_valid:\t(20000, 1)\n"
     ]
    }
   ],
   "source": [
    "    my_obj.load_data()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "48de3301-759b-4211-899d-0d9a4583ac8b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "compiling now\n",
      "training now\n",
      "Epoch 1/200\n",
      "130/130 [==============================] - 1s 3ms/step - loss: 1.5686 - accuracy: 0.0000e+00\n",
      "Epoch 2/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 1.5326 - accuracy: 0.0000e+00\n",
      "Epoch 3/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 1.4938 - accuracy: 0.0000e+00\n",
      "Epoch 4/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 1.3799 - accuracy: 0.0000e+00\n",
      "Epoch 5/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 1.1133 - accuracy: 0.0000e+00\n",
      "Epoch 6/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.7842 - accuracy: 0.0000e+00\n",
      "Epoch 7/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.5830 - accuracy: 0.0000e+00\n",
      "Epoch 8/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.4705 - accuracy: 0.0000e+00\n",
      "Epoch 9/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.3722 - accuracy: 0.0000e+00\n",
      "Epoch 10/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.2765 - accuracy: 0.0000e+00\n",
      "Epoch 11/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.1916 - accuracy: 0.0000e+00\n",
      "Epoch 12/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.1276 - accuracy: 0.0000e+00\n",
      "Epoch 13/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0908 - accuracy: 0.0000e+00\n",
      "Epoch 14/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0763 - accuracy: 0.0000e+00\n",
      "Epoch 15/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0670 - accuracy: 0.0000e+00\n",
      "Epoch 16/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0630 - accuracy: 0.0000e+00\n",
      "Epoch 17/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0590 - accuracy: 0.0000e+00\n",
      "Epoch 18/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0560 - accuracy: 0.0000e+00\n",
      "Epoch 19/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0543 - accuracy: 0.0000e+00\n",
      "Epoch 20/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0521 - accuracy: 0.0000e+00\n",
      "Epoch 21/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0502 - accuracy: 0.0000e+00\n",
      "Epoch 22/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0483 - accuracy: 0.0000e+00\n",
      "Epoch 23/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0468 - accuracy: 0.0000e+00\n",
      "Epoch 24/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0441 - accuracy: 0.0000e+00\n",
      "Epoch 25/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0427 - accuracy: 0.0000e+00\n",
      "Epoch 26/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0406 - accuracy: 0.0000e+00\n",
      "Epoch 27/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0390 - accuracy: 0.0000e+00\n",
      "Epoch 28/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0376 - accuracy: 0.0000e+00\n",
      "Epoch 29/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0356 - accuracy: 0.0000e+00\n",
      "Epoch 30/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0346 - accuracy: 0.0000e+00\n",
      "Epoch 31/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0327 - accuracy: 0.0000e+00\n",
      "Epoch 32/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0312 - accuracy: 0.0000e+00\n",
      "Epoch 33/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0300 - accuracy: 0.0000e+00\n",
      "Epoch 34/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0290 - accuracy: 0.0000e+00\n",
      "Epoch 35/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0271 - accuracy: 0.0000e+00\n",
      "Epoch 36/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0258 - accuracy: 0.0000e+00\n",
      "Epoch 37/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0256 - accuracy: 0.0000e+00\n",
      "Epoch 38/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0232 - accuracy: 0.0000e+00\n",
      "Epoch 39/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0224 - accuracy: 0.0000e+00\n",
      "Epoch 40/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0216 - accuracy: 0.0000e+00\n",
      "Epoch 41/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0204 - accuracy: 0.0000e+00\n",
      "Epoch 42/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0197 - accuracy: 0.0000e+00\n",
      "Epoch 43/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0185 - accuracy: 0.0000e+00\n",
      "Epoch 44/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0180 - accuracy: 0.0000e+00\n",
      "Epoch 45/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0169 - accuracy: 0.0000e+00\n",
      "Epoch 46/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0162 - accuracy: 0.0000e+00\n",
      "Epoch 47/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0159 - accuracy: 0.0000e+00\n",
      "Epoch 48/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0149 - accuracy: 0.0000e+00\n",
      "Epoch 49/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0144 - accuracy: 0.0000e+00\n",
      "Epoch 50/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0146 - accuracy: 0.0000e+00\n",
      "Epoch 51/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0134 - accuracy: 0.0000e+00\n",
      "Epoch 52/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0127 - accuracy: 0.0000e+00\n",
      "Epoch 53/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0125 - accuracy: 0.0000e+00\n",
      "Epoch 54/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0118 - accuracy: 0.0000e+00\n",
      "Epoch 55/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0114 - accuracy: 0.0000e+00\n",
      "Epoch 56/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0113 - accuracy: 0.0000e+00\n",
      "Epoch 57/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0111 - accuracy: 0.0000e+00\n",
      "Epoch 58/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0105 - accuracy: 0.0000e+00\n",
      "Epoch 59/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0103 - accuracy: 0.0000e+00\n",
      "Epoch 60/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0098 - accuracy: 0.0000e+00\n",
      "Epoch 61/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0095 - accuracy: 0.0000e+00\n",
      "Epoch 62/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0091 - accuracy: 0.0000e+00\n",
      "Epoch 63/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0089 - accuracy: 0.0000e+00\n",
      "Epoch 64/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0088 - accuracy: 0.0000e+00\n",
      "Epoch 65/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0081 - accuracy: 0.0000e+00\n",
      "Epoch 66/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0079 - accuracy: 0.0000e+00\n",
      "Epoch 67/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0079 - accuracy: 0.0000e+00\n",
      "Epoch 68/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0075 - accuracy: 0.0000e+00\n",
      "Epoch 69/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0070 - accuracy: 0.0000e+00\n",
      "Epoch 70/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0070 - accuracy: 0.0000e+00\n",
      "Epoch 71/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0070 - accuracy: 0.0000e+00\n",
      "Epoch 72/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0065 - accuracy: 0.0000e+00\n",
      "Epoch 73/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0063 - accuracy: 0.0000e+00\n",
      "Epoch 74/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0059 - accuracy: 0.0000e+00\n",
      "Epoch 75/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0061 - accuracy: 0.0000e+00\n",
      "Epoch 76/200\n",
      "130/130 [==============================] - 0s 4ms/step - loss: 0.0058 - accuracy: 0.0000e+00\n",
      "Epoch 77/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0056 - accuracy: 0.0000e+00\n",
      "Epoch 78/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0054 - accuracy: 0.0000e+00\n",
      "Epoch 79/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0054 - accuracy: 0.0000e+00\n",
      "Epoch 80/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0056 - accuracy: 0.0000e+00\n",
      "Epoch 81/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0047 - accuracy: 0.0000e+00\n",
      "Epoch 82/200\n",
      "130/130 [==============================] - 0s 4ms/step - loss: 0.0044 - accuracy: 0.0000e+00\n",
      "Epoch 83/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0046 - accuracy: 0.0000e+00\n",
      "Epoch 84/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0045 - accuracy: 0.0000e+00\n",
      "Epoch 85/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0042 - accuracy: 0.0000e+00\n",
      "Epoch 86/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0044 - accuracy: 0.0000e+00\n",
      "Epoch 87/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0039 - accuracy: 0.0000e+00\n",
      "Epoch 88/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0040 - accuracy: 0.0000e+00\n",
      "Epoch 89/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0037 - accuracy: 0.0000e+00\n",
      "Epoch 90/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0038 - accuracy: 0.0000e+00\n",
      "Epoch 91/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0036 - accuracy: 0.0000e+00\n",
      "Epoch 92/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0034 - accuracy: 0.0000e+00\n",
      "Epoch 93/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0034 - accuracy: 0.0000e+00\n",
      "Epoch 94/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0033 - accuracy: 0.0000e+00\n",
      "Epoch 95/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0032 - accuracy: 0.0000e+00\n",
      "Epoch 96/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0031 - accuracy: 0.0000e+00\n",
      "Epoch 97/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0029 - accuracy: 0.0000e+00\n",
      "Epoch 98/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0029 - accuracy: 0.0000e+00\n",
      "Epoch 99/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0029 - accuracy: 0.0000e+00\n",
      "Epoch 100/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0028 - accuracy: 0.0000e+00\n",
      "Epoch 101/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0029 - accuracy: 0.0000e+00\n",
      "Epoch 102/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0029 - accuracy: 0.0000e+00\n",
      "Epoch 103/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0027 - accuracy: 0.0000e+00\n",
      "Epoch 104/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0024 - accuracy: 0.0000e+00\n",
      "Epoch 105/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0027 - accuracy: 0.0000e+00\n",
      "Epoch 106/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0024 - accuracy: 0.0000e+00\n",
      "Epoch 107/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0023 - accuracy: 0.0000e+00\n",
      "Epoch 108/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0026 - accuracy: 0.0000e+00\n",
      "Epoch 109/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0025 - accuracy: 0.0000e+00\n",
      "Epoch 110/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0024 - accuracy: 0.0000e+00\n",
      "Epoch 111/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0022 - accuracy: 0.0000e+00\n",
      "Epoch 112/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0021 - accuracy: 0.0000e+00\n",
      "Epoch 113/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0023 - accuracy: 0.0000e+00\n",
      "Epoch 114/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0022 - accuracy: 0.0000e+00\n",
      "Epoch 115/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0023 - accuracy: 0.0000e+00\n",
      "Epoch 116/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0022 - accuracy: 0.0000e+00\n",
      "Epoch 117/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0023 - accuracy: 0.0000e+00\n",
      "Epoch 118/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0022 - accuracy: 0.0000e+00\n",
      "Epoch 119/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0020 - accuracy: 0.0000e+00\n",
      "Epoch 120/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0019 - accuracy: 0.0000e+00\n",
      "Epoch 121/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0019 - accuracy: 0.0000e+00\n",
      "Epoch 122/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0021 - accuracy: 0.0000e+00\n",
      "Epoch 123/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0020 - accuracy: 0.0000e+00\n",
      "Epoch 124/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0020 - accuracy: 0.0000e+00\n",
      "Epoch 125/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0019 - accuracy: 0.0000e+00\n",
      "Epoch 126/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0020 - accuracy: 0.0000e+00\n",
      "Epoch 127/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0019 - accuracy: 0.0000e+00\n",
      "Epoch 128/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0018 - accuracy: 0.0000e+00\n",
      "Epoch 129/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0018 - accuracy: 0.0000e+00\n",
      "Epoch 130/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0020 - accuracy: 0.0000e+00\n",
      "Epoch 131/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0017 - accuracy: 0.0000e+00\n",
      "Epoch 132/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0019 - accuracy: 0.0000e+00\n",
      "Epoch 133/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0017 - accuracy: 0.0000e+00\n",
      "Epoch 134/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0019 - accuracy: 0.0000e+00\n",
      "Epoch 135/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0017 - accuracy: 0.0000e+00\n",
      "Epoch 136/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0017 - accuracy: 0.0000e+00\n",
      "Epoch 137/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 138/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0017 - accuracy: 0.0000e+00\n",
      "Epoch 139/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0017 - accuracy: 0.0000e+00\n",
      "Epoch 140/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0018 - accuracy: 0.0000e+00\n",
      "Epoch 141/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0020 - accuracy: 0.0000e+00\n",
      "Epoch 142/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0016 - accuracy: 0.0000e+00\n",
      "Epoch 143/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0017 - accuracy: 0.0000e+00\n",
      "Epoch 144/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0017 - accuracy: 0.0000e+00\n",
      "Epoch 145/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0016 - accuracy: 0.0000e+00\n",
      "Epoch 146/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0016 - accuracy: 0.0000e+00\n",
      "Epoch 147/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 148/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0016 - accuracy: 0.0000e+00\n",
      "Epoch 149/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0017 - accuracy: 0.0000e+00\n",
      "Epoch 150/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0017 - accuracy: 0.0000e+00\n",
      "Epoch 151/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 152/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0016 - accuracy: 0.0000e+00\n",
      "Epoch 153/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 154/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 155/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 156/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0019 - accuracy: 0.0000e+00\n",
      "Epoch 157/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 158/200\n",
      "130/130 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 159/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0016 - accuracy: 0.0000e+00\n",
      "Epoch 160/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0016 - accuracy: 0.0000e+00\n",
      "Epoch 161/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 162/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0018 - accuracy: 0.0000e+00\n",
      "Epoch 163/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 164/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0012 - accuracy: 0.0000e+00\n",
      "Epoch 165/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0016 - accuracy: 0.0000e+00\n",
      "Epoch 166/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 167/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 168/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 169/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 170/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 171/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 172/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 173/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0016 - accuracy: 0.0000e+00\n",
      "Epoch 174/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 175/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 176/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 177/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 178/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0012 - accuracy: 0.0000e+00\n",
      "Epoch 179/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 180/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 181/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 182/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 183/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 184/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 185/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 186/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 187/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0015 - accuracy: 0.0000e+00\n",
      "Epoch 188/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0012 - accuracy: 0.0000e+00\n",
      "Epoch 189/200\n",
      "130/130 [==============================] - 0s 4ms/step - loss: 0.0012 - accuracy: 0.0000e+00\n",
      "Epoch 190/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 191/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0012 - accuracy: 0.0000e+00\n",
      "Epoch 192/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n",
      "Epoch 193/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 194/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 195/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 196/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0013 - accuracy: 0.0000e+00\n",
      "Epoch 197/200\n",
      "130/130 [==============================] - 0s 3ms/step - loss: 0.0012 - accuracy: 0.0000e+00\n",
      "Epoch 198/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0011 - accuracy: 0.0000e+00\n",
      "Epoch 199/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0012 - accuracy: 0.0000e+00\n",
      "Epoch 200/200\n",
      "130/130 [==============================] - 0s 2ms/step - loss: 0.0014 - accuracy: 0.0000e+00\n"
     ]
    }
   ],
   "source": [
    "    my_obj.train_now()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "cdf1bb9c-f7e7-4012-a607-90273d4f4dbc",
   "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": [
    "    my_obj.predict_now()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "05d669e0-5c2c-4329-80c7-5d5bcb8f7801",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}