TensorsWithTF.ipynb (4454B)
1 { 2 "cells": [ 3 { 4 "cell_type": "code", 5 "execution_count": 16, 6 "metadata": {}, 7 "outputs": [ 8 { 9 "data": { 10 "text/plain": [ 11 "<tf.Tensor: shape=(2, 2), dtype=float32, numpy=\n", 12 "array([[1., 2.],\n", 13 " [4., 5.]], dtype=float32)>" 14 ] 15 }, 16 "execution_count": 16, 17 "metadata": {}, 18 "output_type": "execute_result" 19 } 20 ], 21 "source": [ 22 "import tensorflow as tf\n", 23 "\n", 24 "t = tf.constant([[1.,2.], [4.,5]])\n", 25 "t" 26 ] 27 }, 28 { 29 "cell_type": "code", 30 "execution_count": 17, 31 "metadata": {}, 32 "outputs": [ 33 { 34 "data": { 35 "text/plain": [ 36 "(TensorShape([2, 2]), tf.float32)" 37 ] 38 }, 39 "execution_count": 17, 40 "metadata": {}, 41 "output_type": "execute_result" 42 } 43 ], 44 "source": [ 45 "t.shape, t.dtype" 46 ] 47 }, 48 { 49 "cell_type": "code", 50 "execution_count": 18, 51 "metadata": {}, 52 "outputs": [ 53 { 54 "data": { 55 "text/plain": [ 56 "<tf.Tensor: shape=(2, 2), dtype=float32, numpy=\n", 57 "array([[1., 4.],\n", 58 " [2., 5.]], dtype=float32)>" 59 ] 60 }, 61 "execution_count": 18, 62 "metadata": {}, 63 "output_type": "execute_result" 64 } 65 ], 66 "source": [ 67 "tf.transpose(t)" 68 ] 69 }, 70 { 71 "cell_type": "code", 72 "execution_count": 19, 73 "metadata": {}, 74 "outputs": [ 75 { 76 "data": { 77 "text/plain": [ 78 "<tf.Tensor: shape=(2, 2), dtype=float32, numpy=\n", 79 "array([[ 5., 14.],\n", 80 " [14., 41.]], dtype=float32)>" 81 ] 82 }, 83 "execution_count": 19, 84 "metadata": {}, 85 "output_type": "execute_result" 86 } 87 ], 88 "source": [ 89 "t @ tf.transpose(t)" 90 ] 91 }, 92 { 93 "cell_type": "code", 94 "execution_count": 20, 95 "metadata": {}, 96 "outputs": [ 97 { 98 "data": { 99 "text/plain": [ 100 "<tf.Tensor: shape=(2, 2), dtype=float32, numpy=\n", 101 "array([[-1.6666667 , 0.6666667 ],\n", 102 " [ 1.3333334 , -0.33333334]], dtype=float32)>" 103 ] 104 }, 105 "execution_count": 20, 106 "metadata": {}, 107 "output_type": "execute_result" 108 } 109 ], 110 "source": [ 111 "tf.linalg.inv(t)" 112 ] 113 }, 114 { 115 "cell_type": "code", 116 "execution_count": 23, 117 "metadata": {}, 118 "outputs": [ 119 { 120 "data": { 121 "text/plain": [ 122 "<tf.Tensor: shape=(), dtype=float32, numpy=12.0>" 123 ] 124 }, 125 "execution_count": 23, 126 "metadata": {}, 127 "output_type": "execute_result" 128 } 129 ], 130 "source": [ 131 "tf.reduce_sum(t)" 132 ] 133 }, 134 { 135 "cell_type": "code", 136 "execution_count": 27, 137 "metadata": {}, 138 "outputs": [ 139 { 140 "data": { 141 "text/plain": [ 142 "<tf.Tensor: shape=(2,), dtype=float64, numpy=array([2., 4.])>" 143 ] 144 }, 145 "execution_count": 27, 146 "metadata": {}, 147 "output_type": "execute_result" 148 } 149 ], 150 "source": [ 151 "import numpy as np\n", 152 "a = np.array([2.,4.])\n", 153 "tf.constant(a)" 154 ] 155 }, 156 { 157 "cell_type": "code", 158 "execution_count": 29, 159 "metadata": {}, 160 "outputs": [ 161 { 162 "data": { 163 "text/plain": [ 164 "array([[1., 2.],\n", 165 " [4., 5.]], dtype=float32)" 166 ] 167 }, 168 "execution_count": 29, 169 "metadata": {}, 170 "output_type": "execute_result" 171 } 172 ], 173 "source": [ 174 "t.numpy()" 175 ] 176 }, 177 { 178 "cell_type": "code", 179 "execution_count": 30, 180 "metadata": {}, 181 "outputs": [ 182 { 183 "data": { 184 "text/plain": [ 185 "<tf.Tensor: shape=(2,), dtype=float64, numpy=array([ 4., 16.])>" 186 ] 187 }, 188 "execution_count": 30, 189 "metadata": {}, 190 "output_type": "execute_result" 191 } 192 ], 193 "source": [ 194 "tf.square(a)" 195 ] 196 }, 197 { 198 "cell_type": "code", 199 "execution_count": 31, 200 "metadata": {}, 201 "outputs": [ 202 { 203 "data": { 204 "text/plain": [ 205 "array([[ 1., 4.],\n", 206 " [16., 25.]], dtype=float32)" 207 ] 208 }, 209 "execution_count": 31, 210 "metadata": {}, 211 "output_type": "execute_result" 212 } 213 ], 214 "source": [ 215 "np.square(t)" 216 ] 217 } 218 ], 219 "metadata": { 220 "kernelspec": { 221 "display_name": ".venv", 222 "language": "python", 223 "name": "python3" 224 }, 225 "language_info": { 226 "codemirror_mode": { 227 "name": "ipython", 228 "version": 3 229 }, 230 "file_extension": ".py", 231 "mimetype": "text/x-python", 232 "name": "python", 233 "nbconvert_exporter": "python", 234 "pygments_lexer": "ipython3", 235 "version": "3.11.2" 236 } 237 }, 238 "nbformat": 4, 239 "nbformat_minor": 2 240 }