CholeskyDecomposition.ipynb

untitled3.ipynb

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      "name": "Untitled3.ipynb",
      "version": "0.3.2",
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      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/gist/Kriyszig/1f526570eb11da3ef1e30dd6b3934b93/untitled3.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "metadata": {
        "id": "2RzCFs4p-w1Y",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import tensorflow as tf"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
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        "colab_type": "code",
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      "cell_type": "code",
      "source": [
        "sess = tf.InteractiveSession()\n",
        "inp = tf.Variable([[4,12,16],[12,37,43],[-16,-43,98]])\n",
        "init_op = tf.global_variables_initializer()\n",
        "sess.run(init_op)\n",
        "j = tf.linalg.cholesky(tf.dtypes.cast(inp, dtype=tf.float32))\n",
        "print(j.eval())\n",
        "print(tf.linalg.matmul(j,j, transpose_b = True).eval())\n",
        "sess.close()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[ 2.  0.  0.]\n",
            " [ 6.  1.  0.]\n",
            " [-8.  5.  3.]]\n",
            "[[  4.  12. -16.]\n",
            " [ 12.  37. -43.]\n",
            " [-16. -43.  98.]]\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}