{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pre samog čuvanja modela, potrebno je kreirati i obučiti željeni model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<keras.engine.functional.Functional object at 0x000001B0AA821550>\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "\n",
    "\n",
    "datainput=tf.keras.Input(shape=(32,))\n",
    "dataoutput=tf.keras.layers.Dense(1)(datainput)\n",
    "\n",
    "model=tf.keras.Model(datainput,dataoutput)\n",
    "\n",
    "model.compile(optimizer='adam',loss=\"mean_squared_error\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nakon kreiranja, potrebno je izvršiti trening kreiranog modela"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Za trening će se koristiti nasumicno generisani skup brojeva"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=np.random.random((128,32))\n",
    "y=np.random.random((128,1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nakon generisanja, moguće je izvršiti trening "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4/4 [==============================] - 0s 3ms/step - loss: 0.6013\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x1b0a99bbf10>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(x,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Kreiranje h5 fajla se izvršava pozivanjem sledeceg koda:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: primer.onnx\\assets\n"
     ]
    }
   ],
   "source": [
    "model.save(\"primer.h5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Učitavanje postojećeg fajla može se izvršiti pozivanjem sledećeg koda:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "model2=tf.keras.models.load_model('primer.h5')"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "aa60dac3a75d8da79a838f0110309d30613c15866a87f648d4b1206eac7c83af"
  },
  "kernelspec": {
   "display_name": "Python 3.9.10 64-bit (windows store)",
   "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": "3.9.10"
  },
  "orig_nbformat": 4
 },
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 "nbformat_minor": 2
}