Lab_03_tensorflow_Intro.ipynb

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      "authorship_tag": "ABX9TyNLKC92yjvTewmk83Pe5gJX",
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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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/github/ksathperera/MLOM/blob/main/Lab_03_tensorflow_Intro.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nTJ0ZBoVnpkG",
        "outputId": "7e191170-2f29-4e86-be16-55218a0acb5b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<module 'tensorflow._api.v2.version' from '/usr/local/lib/python3.10/dist-packages/tensorflow/_api/v2/version/__init__.py'>\n"
          ]
        }
      ],
      "source": [
        "import tensorflow as tf\n",
        "print(tf.version)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "string = tf.Variable(\"this is a string\", tf.string)\n",
        "number = tf.Variable(324, tf.int16)\n",
        "floating = tf.Variable(3.567, tf.float64)"
      ],
      "metadata": {
        "id": "4eBXTwX-v7rV"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(floating)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MgPlEut2ylMc",
        "outputId": "a3dc91bd-1031-4179-adf5-62ecc69b8c49"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<tf.Variable 'Variable:0' shape=() dtype=float32, numpy=3.567>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tf.rank(number)  #to check the rank/degree of a created number variable"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d8eoFA0Vy1kG",
        "outputId": "da179c87-f588-4c5e-b6dd-18f7e3d05645"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tf.Tensor: shape=(), dtype=int32, numpy=0>"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tf.rank(string)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QlhMK8wY0DeH",
        "outputId": "e599130c-a64a-41ef-d0f9-f79d5fc9d9df"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tf.Tensor: shape=(), dtype=int32, numpy=0>"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tf.rank(floating)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ow7KfQPb0UxO",
        "outputId": "f2866191-4d79-4e1d-84e3-825f65990ae6"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tf.Tensor: shape=(), dtype=int32, numpy=0>"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "rank2_tensor = tf.Variable([[1,2,3], [3, 4,5]], tf.int16)  #there is a 2D array to, let see the dimension of it"
      ],
      "metadata": {
        "id": "uC_0WVy40fsr"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tf.rank(rank2_tensor)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L_ijDK8-05Mt",
        "outputId": "6aff5bd0-f601-48b9-e798-66b6de5650fe"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tf.Tensor: shape=(), dtype=int32, numpy=2>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "rank2_tensor.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SINalBIb09TI",
        "outputId": "b8804483-c739-4e28-98c0-192c05826f41"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TensorShape([2, 3])"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tensor1 = tf.ones([1,2,3]) # tf.ones() creates a shape [1,2,3] tensor full of ones\n",
        "tensor2 = tf.reshape(tensor1, [2,3,1]) # reshape existing data to shape [2,3,1]\n",
        "tensor3 = tf.reshape(tensor2, [3, -1]) # -1 tells the tensor to calculate the size of the dimension in that place and this will reshape the tensor to [3,3]"
      ],
      "metadata": {
        "id": "UwBzCOSZE8K4"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Now let's have a look at our different tensors\n",
        "print(tensor1)\n",
        "print(tensor2)\n",
        "print(tensor3)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aumim3TAGCHP",
        "outputId": "e4b3ff15-9c01-4dd7-a055-72e2547337f2"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tf.Tensor(\n",
            "[[[1. 1. 1.]\n",
            "  [1. 1. 1.]]], shape=(1, 2, 3), dtype=float32)\n",
            "tf.Tensor(\n",
            "[[[1.]\n",
            "  [1.]\n",
            "  [1.]]\n",
            "\n",
            " [[1.]\n",
            "  [1.]\n",
            "  [1.]]], shape=(2, 3, 1), dtype=float32)\n",
            "tf.Tensor(\n",
            "[[1. 1.]\n",
            " [1. 1.]\n",
            " [1. 1.]], shape=(3, 2), dtype=float32)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#creating a 2D tensor\n",
        "matrix = [[1,2,3,4,5],\n",
        "[6,7,8,9,10],\n",
        "[11,12,13,14,15],\n",
        "[16,17,18,19,20]]\n",
        "\n",
        "#shape = [4,5] since there is a 2 dimension matrix\n",
        "\n",
        "tensor = tf.Variable(matrix, dtype=tf.int32)  #create a variable and assign matrix for that variable\n",
        "print(tf.rank(tensor))\n",
        "print(tensor.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M4Gq-n6jGUvK",
        "outputId": "ec89ae4e-e754-4162-a50a-bf841bfe7975"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tf.Tensor(2, shape=(), dtype=int32)\n",
            "(4, 5)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "three = tensor[0,2] # selects the 3rd element from the 1st row\n",
        "print(three) # -> 3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pdtNLfzcKTTB",
        "outputId": "13942410-8cdc-4d0d-dfe2-dfc3242874df"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tf.Tensor(3, shape=(), dtype=int32)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "row1 = tensor[0] # selects the first row\n",
        "print(row1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_zR2FapXL9xV",
        "outputId": "bafec933-9dce-4880-c6db-26670419b5ad"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tf.Tensor([1 2 3 4 5], shape=(5,), dtype=int32)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "column1 = tensor[:, 0] # selects the first column\n",
        "print(column1)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0Ac9NATOMJI9",
        "outputId": "20024d8f-2365-4f2f-bd12-66332522da30"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tf.Tensor([ 1  6 11 16], shape=(4,), dtype=int32)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "column_1_in_row_2_and_3 = tensor[1:3, 0]\n",
        "print(column_1_in_row_2_and_3)"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "gc2gGH-OMQ0U",
        "outputId": "29435166-c777-4248-f623-646a7a0d12d6"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tf.Tensor([ 6 11], shape=(2,), dtype=int32)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "1lmCg6NlM3LP"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}