1-TensorFlow-Basic.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "343f04d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "33db4bb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(2, 2), dtype=int32, numpy=\n",
       "array([[1, 2],\n",
       "       [3, 4]])>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor = tf.constant([\n",
    "    [1, 2],\n",
    "    [3, 4]\n",
    "])\n",
    "tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "44200d44",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.8.0'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "aa969d45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TensorShape([2, 2])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "385f9d12",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "99c4447d",
   "metadata": {},
   "outputs": [],
   "source": [
    "tensor_np = tensor.numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cb8e3c00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2],\n",
       "       [3, 4]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor_np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6f373c90",
   "metadata": {},
   "outputs": [],
   "source": [
    "np_array = np.random.randint(3, 9, size=(3, 3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "351b6a75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[6, 6, 7],\n",
       "       [8, 4, 5],\n",
       "       [4, 7, 7]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "14933bcb",
   "metadata": {},
   "outputs": [],
   "source": [
    "tensor2 = tf.constant(np_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a6539364",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(3, 3), dtype=int32, numpy=\n",
       "array([[6, 6, 7],\n",
       "       [8, 4, 5],\n",
       "       [4, 7, 7]])>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "75d8b349",
   "metadata": {},
   "outputs": [],
   "source": [
    "tf_variable = tf.Variable([\n",
    "    [1.0, 2, 3],\n",
    "    [4, 5, 6]\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0c792d2b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Variable 'Variable:0' shape=(2, 3) dtype=float32, numpy=\n",
       "array([[1., 2., 3.],\n",
       "       [4., 5., 6.]], dtype=float32)>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "97d7a941",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 2., 3.],\n",
       "       [4., 5., 6.]], dtype=float32)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_variable.numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c84d23d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Variable 'UnreadVariable' shape=(2, 3) dtype=float32, numpy=\n",
       "array([[ 1.,  2.,  3.],\n",
       "       [ 4., 40.,  6.]], dtype=float32)>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_variable[1, 1].assign(40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "00a0b4ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Variable 'Variable:0' shape=(2, 3) dtype=float32, numpy=\n",
       "array([[ 1.,  2.,  3.],\n",
       "       [ 4., 40.,  6.]], dtype=float32)>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f128b3b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(2, 2), dtype=int32, numpy=\n",
       "array([[1, 2],\n",
       "       [3, 4]])>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "5c45f1ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(2, 2), dtype=int32, numpy=\n",
       "array([[3, 4],\n",
       "       [5, 6]])>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor + 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c408ee90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(2, 2), dtype=int32, numpy=\n",
       "array([[1, 2],\n",
       "       [3, 4]])>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ae76e55c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(2, 2), dtype=int32, numpy=\n",
       "array([[ 5, 10],\n",
       "       [15, 20]])>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor * 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "960621cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1,  4],\n",
       "       [ 9, 16]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.square(tensor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8cdec494",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 1.41421356],\n",
       "       [1.73205081, 2.        ]])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(tensor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "fe2e0745",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(3, 3), dtype=int32, numpy=\n",
       "array([[6, 6, 7],\n",
       "       [8, 4, 5],\n",
       "       [4, 7, 7]])>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "06720eea",
   "metadata": {},
   "outputs": [],
   "source": [
    "tensor3 = tf.constant(np.random.randint(0, 4, size=(2, 2)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "41794236",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(2, 2), dtype=int32, numpy=\n",
       "array([[1, 3],\n",
       "       [1, 2]])>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e3b30074",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(2, 2), dtype=int32, numpy=\n",
       "array([[ 3,  7],\n",
       "       [ 7, 17]])>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor @ tensor3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "68f0d8b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(2, 2), dtype=int32, numpy=\n",
       "array([[1, 2],\n",
       "       [3, 4]])>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "90d74e26",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(), dtype=string, numpy=b'TF'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_string = tf.constant(\"TF\")\n",
    "tf_string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "2741b3f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(), dtype=int32, numpy=2>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.strings.length(tf_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "405573c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(2,), dtype=int32, numpy=array([84, 70])>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.strings.unicode_decode(tf_string, 'UTF8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "38364339",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "84"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ord('T')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "baa5786f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tf.Tensor(b'TF', shape=(), dtype=string)\n",
      "tf.Tensor(b'is', shape=(), dtype=string)\n",
      "tf.Tensor(b'good', shape=(), dtype=string)\n"
     ]
    }
   ],
   "source": [
    "tf_str_arr = tf.constant([\n",
    "    \"TF\", \"is\", \"good\"\n",
    "])\n",
    "for s in tf_str_arr:\n",
    "    print(s)"
   ]
  }
 ],
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