LA_Ch01_01_Ex.ipynb

la_ch01_01_ex.ipynb

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      "authorship_tag": "ABX9TyPXQu60G8eoCGKjQCmk0O1z",
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      "name": "python3",
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/dsaint31x/88ec4f787feba7df702c89b0cb6fd9ae/la_ch01_01_ex.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
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        },
        "id": "eVLYwK6zE2Gl",
        "outputId": "7529e4c3-3f3d-4154-ab4b-ba633788d36b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tf.Tensor: shape=(3, 1), dtype=float64, numpy=\n",
              "array([[29.],\n",
              "       [16.],\n",
              "       [ 3.]])>"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ],
      "source": [
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "\n",
        "A = np.array([\n",
        "    [1 ,-2, 1],\n",
        "    [0 , 2,-8],\n",
        "    [-4, 5, 9]\n",
        "], dtype=float)\n",
        "\n",
        "cmtx = tf.constant(A)\n",
        "\n",
        "b = np.array([0,8,-9],dtype=float)\n",
        "\n",
        "# tf.constant 를 이용. (1)\n",
        "# b = b.reshape(-1,1)\n",
        "# bvec = tf.constant(b)\n",
        "\n",
        "# tf.constant 를 이용. (2)\n",
        "bvec = tf.constant(b, shape=(3,1))\n",
        "\n",
        "# tf.Varialbe을 이용.\n",
        "# b = b.reshape(-1,1)\n",
        "# bvec = tf.Variable(b, shape=(3,1))\n",
        "\n",
        "solution = tf.linalg.solve(cmtx,bvec)\n",
        "solution"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bvec.shape"
      ],
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        "id": "jBGbf72LGAuJ",
        "outputId": "c14967a0-7697-4bd0-af35-0bfc4cd23a22"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TensorShape([3, 1])"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "A.shape"
      ],
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        "id": "ENpsjTOGGPWQ",
        "outputId": "e024dde2-54c8-44ed-e219-6d229af6c7bd"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    }
  ]
}