1  {
   2   "cells": [
   3    {
   4     "cell_type": "code",
   5     "execution_count": 1,
   6     "id": "d5089f4c",
   7     "metadata": {},
   8     "outputs": [],
   9     "source": [
  10      "import tensorflow as tf"
  11     ]
  12    },
  13    {
  14     "cell_type": "code",
  15     "execution_count": 2,
  16     "id": "2d35ddfb",
  17     "metadata": {},
  18     "outputs": [],
  19     "source": [
  20      "#%tensorflow_version x.x"
  21     ]
  22    },
  23    {
  24     "cell_type": "code",
  25     "execution_count": 3,
  26     "id": "c3f6ddcb",
  27     "metadata": {},
  28     "outputs": [],
  29     "source": [
  30      "s= tf.Variable('abc')"
  31     ]
  32    },
  33    {
  34     "cell_type": "code",
  35     "execution_count": 4,
  36     "id": "969c3fe4",
  37     "metadata": {},
  38     "outputs": [],
  39     "source": [
  40      "import numpy as np\n",
  41      "import sys"
  42     ]
  43    },
  44    {
  45     "cell_type": "code",
  46     "execution_count": null,
  47     "id": "a02b3d7b",
  48     "metadata": {},
  49     "outputs": [],
  50     "source": []
  51    },
  52    {
  53     "cell_type": "code",
  54     "execution_count": 5,
  55     "id": "c7387f28",
  56     "metadata": {},
  57     "outputs": [],
  58     "source": [
  59      "ar= tf.Variable([[1,2,3],[4,5,6],[7,5,6],[7,8,6]])\n",
  60      "br= tf.Variable([['a','b'],['c','d']], tf.string)"
  61     ]
  62    },
  63    {
  64     "cell_type": "code",
  65     "execution_count": 6,
  66     "id": "46fc1da9",
  67     "metadata": {},
  68     "outputs": [
  69      {
  70       "data": {
  71        "text/plain": [
  72         "TensorShape([4, 3])"
  73        ]
  74       },
  75       "execution_count": 6,
  76       "metadata": {},
  77       "output_type": "execute_result"
  78      }
  79     ],
  80     "source": [
  81      "ar.shape"
  82     ]
  83    },
  84    {
  85     "cell_type": "code",
  86     "execution_count": 7,
  87     "id": "7cb14a0f",
  88     "metadata": {},
  89     "outputs": [
  90      {
  91       "data": {
  92        "text/plain": [
  93         "TensorShape([2, 2])"
  94        ]
  95       },
  96       "execution_count": 7,
  97       "metadata": {},
  98       "output_type": "execute_result"
  99      }
 100     ],
 101     "source": [
 102      "br.shape"
 103     ]
 104    },
 105    {
 106     "cell_type": "code",
 107     "execution_count": null,
 108     "id": "8175657a",
 109     "metadata": {},
 110     "outputs": [],
 111     "source": []
 112    },
 113    {
 114     "cell_type": "code",
 115     "execution_count": 8,
 116     "id": "45888d6a",
 117     "metadata": {},
 118     "outputs": [],
 119     "source": [
 120      "ones= tf.ones([2,4])"
 121     ]
 122    },
 123    {
 124     "cell_type": "code",
 125     "execution_count": 9,
 126     "id": "d9d2746a",
 127     "metadata": {},
 128     "outputs": [
 129      {
 130       "name": "stdout",
 131       "output_type": "stream",
 132       "text": [
 133        "[0 1 2 ... 7 8 9]\r\n"
 134       ]
 135      }
 136     ],
 137     "source": [
 138      "tensor = tf.range(10)\n",
 139      "tf.print(tensor, output_stream=sys.stderr)"
 140     ]
 141    },
 142    {
 143     "cell_type": "code",
 144     "execution_count": 10,
 145     "id": "da15bac6",
 146     "metadata": {},
 147     "outputs": [
 148      {
 149       "name": "stdout",
 150       "output_type": "stream",
 151       "text": [
 152        "[0 1 2 ... 7 8 9]\r\n"
 153       ]
 154      }
 155     ],
 156     "source": [
 157      "tensor = tf.range(10)\n",
 158      "tf.print(tensor)"
 159     ]
 160    },
 161    {
 162     "cell_type": "code",
 163     "execution_count": 11,
 164     "id": "ef636feb",
 165     "metadata": {},
 166     "outputs": [
 167      {
 168       "name": "stdout",
 169       "output_type": "stream",
 170       "text": [
 171        "[0 1 2 ... 7 8 9]\r\n"
 172       ]
 173      }
 174     ],
 175     "source": [
 176      "import tensorflow as tf\n",
 177      "import sys\n",
 178      "\n",
 179      "tensor = tf.range(10)\n",
 180      "tf.print(tensor, output_stream=sys.stderr)"
 181     ]
 182    },
 183    {
 184     "cell_type": "code",
 185     "execution_count": 12,
 186     "id": "d263b7d7",
 187     "metadata": {},
 188     "outputs": [],
 189     "source": [
 190      "arr= np.arange(1,31).reshape(-1,2,3)"
 191     ]
 192    },
 193    {
 194     "cell_type": "code",
 195     "execution_count": 13,
 196     "id": "6d428297",
 197     "metadata": {},
 198     "outputs": [],
 199     "source": [
 200      "tensor= tf.Variable(arr)"
 201     ]
 202    },
 203    {
 204     "cell_type": "code",
 205     "execution_count": 14,
 206     "id": "347a39a6",
 207     "metadata": {},
 208     "outputs": [
 209      {
 210       "name": "stdout",
 211       "output_type": "stream",
 212       "text": [
 213        "array([[[ 1,  2,  3],\n",
 214        "        [ 4,  5,  6]],\n",
 215        "\n",
 216        "       [[ 7,  8,  9],\n",
 217        "        [10, 11, 12]],\n",
 218        "\n",
 219        "       [[13, 14, 15],\n",
 220        "        [16, 17, 18]],\n",
 221        "\n",
 222        "       [[19, 20, 21],\n",
 223        "        [22, 23, 24]],\n",
 224        "\n",
 225        "       [[25, 26, 27],\n",
 226        "        [28, 29, 30]]])\r\n"
 227       ]
 228      }
 229     ],
 230     "source": [
 231      "tf.print(arr)"
 232     ]
 233    },
 234    {
 235     "cell_type": "code",
 236     "execution_count": 20,
 237     "id": "1c24f1b8",
 238     "metadata": {},
 239     "outputs": [
 240      {
 241       "data": {
 242        "text/plain": [
 243         "array([[ 9, 12],\n",
 244         "       [15, 18]])"
 245        ]
 246       },
 247       "execution_count": 20,
 248       "metadata": {},
 249       "output_type": "execute_result"
 250      }
 251     ],
 252     "source": [
 253      "arr[1:3,:,-1]"
 254     ]
 255    },
 256    {
 257     "cell_type": "code",
 258     "execution_count": null,
 259     "id": "3dd62479",
 260     "metadata": {},
 261     "outputs": [],
 262     "source": []
 263    }
 264   ],
 265   "metadata": {
 266    "kernelspec": {
 267     "display_name": "Python 3",
 268     "language": "python",
 269     "name": "python3"
 270    },
 271    "language_info": {
 272     "codemirror_mode": {
 273      "name": "ipython",
 274      "version": 3
 275     },
 276     "file_extension": ".py",
 277     "mimetype": "text/x-python",
 278     "name": "python",
 279     "nbconvert_exporter": "python",
 280     "pygments_lexer": "ipython3",
 281     "version": "3.8.8"
 282    }
 283   },
 284   "nbformat": 4,
 285   "nbformat_minor": 5
 286  }
 287