TensorFlow Eager Execution

Eager_Execution_Disabled.ipynb

Eager_Execution_Enabled.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Eager_execution.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "8bzIFsLrNz3e",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import tensorflow as tf\n",
        "\n",
        "tf.compat.v1.enable_eager_execution()\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "joWTC7PzPIW_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "2fc5b6b5-b691-484c-aedd-f47f0140be4b"
      },
      "source": [
        "tf.executing_eagerly()"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "attributes": {
          "classes": [
            "py"
          ],
          "id": ""
        },
        "colab_type": "code",
        "outputId": "ccfd13ce-8d79-4765-bafb-7a9e6bb4132f",
        "id": "vSTmGyALNcUn",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "x = [[2.]]\n",
        "m = tf.matmul(x, x)\n",
        "print(\"hello, {}\".format(m))"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "hello, [[4.]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "outputId": "d9f77cf9-e100-4492-eec3-85875ffb6fd7",
        "id": "xk136sOrNcUq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "source": [
        "a = tf.constant([[1, 2],[3, 4]])\n",
        "print(a)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tf.Tensor(\n",
            "[[1 2]\n",
            " [3 4]], shape=(2, 2), dtype=int32)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "attributes": {
          "classes": [
            "py"
          ],
          "id": ""
        },
        "colab_type": "code",
        "id": "Ui025t1qqEfm",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "cda5a93b-432e-42e3-d5b7-ef1bdae58f1e"
      },
      "source": [
        "# Use NumPy values\n",
        "import numpy as np\n",
        "\n",
        "c = np.multiply(a, a)\n",
        "print(c)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[ 1  4]\n",
            " [ 9 16]]\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}