Colab 2 - Introducción a TensorFlow 2.0 .ipynb

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   "source": [
    "<a href=\"https://colab.research.google.com/github/joanby/tensorflow2/blob/master/Colab%202%20-%20Introducción%20a%20TensorFlow%202.0%20.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "kqnQhKafgyZC"
   },
   "source": [
    "## TensorFlow 1.X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SiauG1locQIa"
   },
   "source": [
    "### Instalar TensorFlow 1.X\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Especificando la versión de TensorFlow\n",
    "\n",
    "Ejecutando \"importar tensorflow\" importará la versión por defecto (actualmente 2.x). Puedes usar la 1.x ejecutando una celda con la \"versión mágica de tensorflow\" **antes de ejecutar \"importar tensorflow\".\n",
    "\n",
    "### Si no funciona hacer el pip install\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 940
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 82749,
     "status": "ok",
     "timestamp": 1564562087441,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
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      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "iVM4JRo8cJ0e",
    "outputId": "4d03d53c-02bc-43b4-b951-e2a36738e5e8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting tensorflow-gpu==1.13.1\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/7b/b1/0ad4ae02e17ddd62109cd54c291e311c4b5fd09b4d0678d3d6ce4159b0f0/tensorflow_gpu-1.13.1-cp36-cp36m-manylinux1_x86_64.whl (345.2MB)\n",
      "\u001b[K     |████████████████████████████████| 345.2MB 62kB/s \n",
      "\u001b[?25hRequirement already satisfied: keras-preprocessing>=1.0.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (1.1.0)\n",
      "Requirement already satisfied: gast>=0.2.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (0.2.2)\n",
      "Requirement already satisfied: protobuf>=3.6.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (3.7.1)\n",
      "Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (0.33.4)\n",
      "Requirement already satisfied: grpcio>=1.8.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (1.15.0)\n",
      "Requirement already satisfied: keras-applications>=1.0.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (1.0.8)\n",
      "Requirement already satisfied: absl-py>=0.1.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (0.7.1)\n",
      "Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (1.12.0)\n",
      "Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (1.1.0)\n",
      "Collecting tensorboard<1.14.0,>=1.13.0 (from tensorflow-gpu==1.13.1)\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/0f/39/bdd75b08a6fba41f098b6cb091b9e8c7a80e1b4d679a581a0ccd17b10373/tensorboard-1.13.1-py3-none-any.whl (3.2MB)\n",
      "\u001b[K     |████████████████████████████████| 3.2MB 30.1MB/s \n",
      "\u001b[?25hRequirement already satisfied: astor>=0.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (0.8.0)\n",
      "Requirement already satisfied: numpy>=1.13.3 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.13.1) (1.16.4)\n",
      "Collecting tensorflow-estimator<1.14.0rc0,>=1.13.0 (from tensorflow-gpu==1.13.1)\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/bb/48/13f49fc3fa0fdf916aa1419013bb8f2ad09674c275b4046d5ee669a46873/tensorflow_estimator-1.13.0-py2.py3-none-any.whl (367kB)\n",
      "\u001b[K     |████████████████████████████████| 368kB 45.5MB/s \n",
      "\u001b[?25hRequirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.6.1->tensorflow-gpu==1.13.1) (41.0.1)\n",
      "Requirement already satisfied: h5py in /usr/local/lib/python3.6/dist-packages (from keras-applications>=1.0.6->tensorflow-gpu==1.13.1) (2.8.0)\n",
      "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.14.0,>=1.13.0->tensorflow-gpu==1.13.1) (0.15.5)\n",
      "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.14.0,>=1.13.0->tensorflow-gpu==1.13.1) (3.1.1)\n",
      "Collecting mock>=2.0.0 (from tensorflow-estimator<1.14.0rc0,>=1.13.0->tensorflow-gpu==1.13.1)\n",
      "  Downloading https://files.pythonhosted.org/packages/05/d2/f94e68be6b17f46d2c353564da56e6fb89ef09faeeff3313a046cb810ca9/mock-3.0.5-py2.py3-none-any.whl\n",
      "\u001b[31mERROR: tensorflow 1.14.0 has requirement tensorboard<1.15.0,>=1.14.0, but you'll have tensorboard 1.13.1 which is incompatible.\u001b[0m\n",
      "\u001b[31mERROR: tensorflow 1.14.0 has requirement tensorflow-estimator<1.15.0rc0,>=1.14.0rc0, but you'll have tensorflow-estimator 1.13.0 which is incompatible.\u001b[0m\n",
      "Installing collected packages: tensorboard, mock, tensorflow-estimator, tensorflow-gpu\n",
      "  Found existing installation: tensorboard 1.14.0\n",
      "    Uninstalling tensorboard-1.14.0:\n",
      "      Successfully uninstalled tensorboard-1.14.0\n",
      "  Found existing installation: tensorflow-estimator 1.14.0\n",
      "    Uninstalling tensorflow-estimator-1.14.0:\n",
      "      Successfully uninstalled tensorflow-estimator-1.14.0\n",
      "Successfully installed mock-3.0.5 tensorboard-1.13.1 tensorflow-estimator-1.13.0 tensorflow-gpu-1.13.1\n"
     ]
    }
   ],
   "source": [
    "#!pip install tensorflow==1.13.1\n",
    "%tensorflow_version 1.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "XQcq7zJ4cgf_"
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1000,
     "status": "ok",
     "timestamp": 1564562113172,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "IKzynmqddNBO",
    "outputId": "ba49e242-03bb-430c-c8b0-5c4f67b7973f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.13.1'"
      ]
     },
     "execution_count": 3,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "kyvi9fbgfNXO"
   },
   "source": [
    "### Constantes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "tSSEoeadsbn5"
   },
   "source": [
    "#### Definir una constante"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "UCnWxoK3e1rm"
   },
   "outputs": [],
   "source": [
    "# Definir una constante en TensorFlow\n",
    "tensor = tf.constant([[23, 4], [32, 51]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 661,
     "status": "ok",
     "timestamp": 1564562161687,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
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      "userId": "03106941341701838274"
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     "user_tz": -120
    },
    "id": "_6YBDabufXO1",
    "outputId": "2eb60122-bb29-491e-8a4d-7db5bbfa7b8b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor 'Const:0' shape=(2, 2) dtype=int32>"
      ]
     },
     "execution_count": 5,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 347
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 523,
     "status": "error",
     "timestamp": 1564562186405,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "RdNftutxfZ5N",
    "outputId": "3b06d84c-18e6-4ba8-e820-3909f354cd43"
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "ignored",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-6-16de3a9398ce>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtensor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py\u001b[0m in \u001b[0;36meval\u001b[0;34m(self, feed_dict, session)\u001b[0m\n\u001b[1;32m    693\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    694\u001b[0m     \"\"\"\n\u001b[0;32m--> 695\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_eval_using_default_session\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfeed_dict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgraph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msession\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    696\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    697\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py\u001b[0m in \u001b[0;36m_eval_using_default_session\u001b[0;34m(tensors, feed_dict, graph, session)\u001b[0m\n\u001b[1;32m   5165\u001b[0m     \u001b[0msession\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_default_session\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5166\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0msession\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5167\u001b[0;31m       raise ValueError(\"Cannot evaluate tensor using `eval()`: No default \"\n\u001b[0m\u001b[1;32m   5168\u001b[0m                        \u001b[0;34m\"session is registered. Use `with \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5169\u001b[0m                        \u001b[0;34m\"sess.as_default()` or pass an explicit session to \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Cannot evaluate tensor using `eval()`: No default session is registered. Use `with sess.as_default()` or pass an explicit session to `eval(session=sess)`"
     ]
    }
   ],
   "source": [
    "# Si la session no ha sido inicializada, no se pueden acceder a los valores de la constante\n",
    "tensor.eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "E-VQJUFxf9fU"
   },
   "source": [
    "#### Consultar los valores de la constante"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "MlHowT2SgDmt"
   },
   "outputs": [],
   "source": [
    "session = tf.Session()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "iM9jQMJhgGzi"
   },
   "outputs": [],
   "source": [
    "session.run(tf.global_variables_initializer())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Xk-Ng1_0fmeV"
   },
   "outputs": [],
   "source": [
    "tensor_value = session.run(tensor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 635,
     "status": "ok",
     "timestamp": 1564562211234,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "4c_EfA0zgBb9",
    "outputId": "652a35ee-e97b-4f5a-b04f-42edddf331d4"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[23,  4],\n",
       "       [32, 51]], dtype=int32)"
      ]
     },
     "execution_count": 10,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor_value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "UAE50vlcdasP"
   },
   "source": [
    "### Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "-C8yhSZksm1R"
   },
   "source": [
    "#### Definir una variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 88
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 654,
     "status": "ok",
     "timestamp": 1564562259396,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "Tex4Ud2JdOe9",
    "outputId": "b772a269-0721-4478-dbcd-7cad9c2027a5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n"
     ]
    }
   ],
   "source": [
    "# Definir una variable de TensorFlow \n",
    "variable = tf.Variable([[30, 20], [10, 45]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1198,
     "status": "ok",
     "timestamp": 1564562267026,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "YMco0fladtkt",
    "outputId": "92d839a4-ef8f-4905-d823-3a86171b8c91"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Variable 'Variable:0' shape=(2, 2) dtype=int32_ref>"
      ]
     },
     "execution_count": 12,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 164
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 727,
     "status": "error",
     "timestamp": 1564562587660,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "OAZRkgwed9X-",
    "outputId": "43668b12-19f3-424f-b61e-1eb07dcb22e7"
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "ignored",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-37927263c520>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mvariable\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'variable' is not defined"
     ]
    }
   ],
   "source": [
    "# Si la session no ha sido inicializada, no se podrán acceder a los valores de la variable\n",
    "variable.eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "lsguZm4gep9g"
   },
   "source": [
    "#### Consultar los valores de una variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "8Nwg0W4LedDW"
   },
   "outputs": [],
   "source": [
    "# Inicializar una session\n",
    "session = tf.Session()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "UnPhvNt1eu_e"
   },
   "outputs": [],
   "source": [
    "# Inicializar TODAS las variables de la session\n",
    "session.run(tf.global_variables_initializer())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 164
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 764,
     "status": "error",
     "timestamp": 1564562551938,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "yMmNCDviex--",
    "outputId": "919f781c-57ed-44f6-d462-835c52c8005f"
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "ignored",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-6-d783cfc74c70>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mvariable\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msession\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'variable' is not defined"
     ]
    }
   ],
   "source": [
    "# Ejecutar el método eval en el entorno con la sesión iniciada para recuperar los valores del mismo\n",
    "variable.eval(session)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "wJ6s9hH5gsvW"
   },
   "source": [
    "## TensorFlow 2.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Zl7ADLJ_g38A"
   },
   "source": [
    "### Instalar TensorFlow 2.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 920
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 78807,
     "status": "ok",
     "timestamp": 1564562400796,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "XExgAvb-gkb9",
    "outputId": "e697d6f4-a24c-4a2d-ffef-04c03f1f4435"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting tensorflow-gpu==2.0.0-alpha0\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/1a/66/32cffad095253219d53f6b6c2a436637bbe45ac4e7be0244557210dc3918/tensorflow_gpu-2.0.0a0-cp36-cp36m-manylinux1_x86_64.whl (332.1MB)\n",
      "\u001b[K     |████████████████████████████████| 332.1MB 55kB/s \n",
      "\u001b[?25hRequirement already satisfied: google-pasta>=0.1.2 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (0.1.7)\n",
      "Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.1.0)\n",
      "Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (0.33.4)\n",
      "Requirement already satisfied: protobuf>=3.6.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (3.7.1)\n",
      "Requirement already satisfied: gast>=0.2.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (0.2.2)\n",
      "Requirement already satisfied: numpy<2.0,>=1.14.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.16.4)\n",
      "Collecting tf-estimator-nightly<1.14.0.dev2019030116,>=1.14.0.dev2019030115 (from tensorflow-gpu==2.0.0-alpha0)\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/13/82/f16063b4eed210dc2ab057930ac1da4fbe1e91b7b051a6c8370b401e6ae7/tf_estimator_nightly-1.14.0.dev2019030115-py2.py3-none-any.whl (411kB)\n",
      "\u001b[K     |████████████████████████████████| 419kB 40.5MB/s \n",
      "\u001b[?25hRequirement already satisfied: grpcio>=1.8.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.15.0)\n",
      "Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.12.0)\n",
      "Requirement already satisfied: absl-py>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (0.7.1)\n",
      "Requirement already satisfied: keras-preprocessing>=1.0.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.1.0)\n",
      "Requirement already satisfied: astor>=0.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (0.8.0)\n",
      "Collecting tb-nightly<1.14.0a20190302,>=1.14.0a20190301 (from tensorflow-gpu==2.0.0-alpha0)\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/a9/51/aa1d756644bf4624c03844115e4ac4058eff77acd786b26315f051a4b195/tb_nightly-1.14.0a20190301-py3-none-any.whl (3.0MB)\n",
      "\u001b[K     |████████████████████████████████| 3.0MB 28.7MB/s \n",
      "\u001b[?25hRequirement already satisfied: keras-applications>=1.0.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-alpha0) (1.0.8)\n",
      "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.6.1->tensorflow-gpu==2.0.0-alpha0) (41.0.1)\n",
      "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<1.14.0a20190302,>=1.14.0a20190301->tensorflow-gpu==2.0.0-alpha0) (0.15.5)\n",
      "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<1.14.0a20190302,>=1.14.0a20190301->tensorflow-gpu==2.0.0-alpha0) (3.1.1)\n",
      "Requirement already satisfied: h5py in /usr/local/lib/python3.6/dist-packages (from keras-applications>=1.0.6->tensorflow-gpu==2.0.0-alpha0) (2.8.0)\n",
      "Installing collected packages: tf-estimator-nightly, tb-nightly, tensorflow-gpu\n",
      "  Found existing installation: tensorflow-gpu 1.13.1\n",
      "    Uninstalling tensorflow-gpu-1.13.1:\n",
      "      Successfully uninstalled tensorflow-gpu-1.13.1\n",
      "Successfully installed tb-nightly-1.14.0a20190301 tensorflow-gpu-2.0.0a0 tf-estimator-nightly-1.14.0.dev2019030115\n"
     ]
    },
    {
     "data": {
      "application/vnd.colab-display-data+json": {
       "pip_warning": {
        "packages": [
         "tensorflow",
         "tensorflow_estimator"
        ]
       }
      }
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#!pip install tensorflow-gpu==2.0.0-alpha0\n",
    "%tensorflow_version 2.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ZsQVt3TghDWN"
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 610,
     "status": "ok",
     "timestamp": 1564562453699,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "bjZ7TmxNh3FE",
    "outputId": "e68e8a1b-7996-4086-d9ab-88fadef6527b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.0.0-alpha0'"
      ]
     },
     "execution_count": 2,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "L3jqjCppiB0x"
   },
   "source": [
    "### Constantes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "F58hfumftBPK"
   },
   "source": [
    "#### Definir una constante"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "EL_NS0EDh4U2"
   },
   "outputs": [],
   "source": [
    "# Definir una constante en TensorFlow 2.0\n",
    "tensor_20 = tf.constant([[23, 4], [32, 51]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1032,
     "status": "ok",
     "timestamp": 1564562459777,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "zu1SK9N-iLj-",
    "outputId": "df8f997c-b5d7-4caa-d230-65d2e161f4bc"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: id=0, shape=(2, 2), dtype=int32, numpy=\n",
       "array([[23,  4],\n",
       "       [32, 51]], dtype=int32)>"
      ]
     },
     "execution_count": 4,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor_20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 947,
     "status": "ok",
     "timestamp": 1564562471388,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "Pi1hQ7VYiNoP",
    "outputId": "5d0bd6a8-ddeb-464b-d551-93ae4e0ada83"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TensorShape([2, 2])"
      ]
     },
     "execution_count": 5,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtener el tamaño de un tensor\n",
    "tensor_20.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "KfR8I7EOituB"
   },
   "source": [
    "#### Consultar los valores de una constante"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 668,
     "status": "ok",
     "timestamp": 1564562645359,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "C1mt_C-7iV3l",
    "outputId": "fe14cad5-2070-42c3-e603-5b9ef001a176"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[23,  4],\n",
       "       [32, 51]], dtype=int32)"
      ]
     },
     "execution_count": 9,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtener los valores directamente desde una constante de TensorFlow con numpy, sin necesidad de una session\n",
    "tensor_20.numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "4yu4Rvo2igb2"
   },
   "outputs": [],
   "source": [
    "# Podemos convertir un array de numpy a un tensor de TensorFlow directamente\n",
    "numpy_tensor = np.array([[23,  4], [32, 51]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "3uLZ7XAYjOO2"
   },
   "outputs": [],
   "source": [
    "tensor_from_numpy = tf.constant(numpy_tensor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 766,
     "status": "ok",
     "timestamp": 1564562649962,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "ltsz-6FrjWDE",
    "outputId": "44d79429-d8ec-4596-f9cd-4c4f8c2885f9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: id=3, shape=(2, 2), dtype=int64, numpy=\n",
       "array([[23,  4],\n",
       "       [32, 51]])>"
      ]
     },
     "execution_count": 12,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor_from_numpy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "uq-atYpaV2mB"
   },
   "source": [
    "### Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SzoCDLwlt8V-"
   },
   "source": [
    "#### Definir una variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1088,
     "status": "ok",
     "timestamp": 1564562659804,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "INUlB5zoIB90",
    "outputId": "7deea8af-bb2f-4727-8123-0ef1a9805ae6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Variable 'Variable:0' shape=(2, 3) dtype=float32, numpy=\n",
       "array([[1., 2., 3.],\n",
       "       [4., 5., 6.]], dtype=float32)>"
      ]
     },
     "execution_count": 13,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf2_variable = tf.Variable([[1., 2., 3.], [4., 5., 6.]])\n",
    "tf2_variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Oqi-QOsMWo7F"
   },
   "source": [
    "#### Consultar los valores de una variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 929,
     "status": "ok",
     "timestamp": 1564562677150,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "pCQr70r1IhLF",
    "outputId": "4b9535a7-1c21-4b5c-fca6-f3370487e979"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 2., 3.],\n",
       "       [4., 5., 6.]], dtype=float32)"
      ]
     },
     "execution_count": 14,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf2_variable.numpy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Ka8Tpnk_WvET"
   },
   "source": [
    "#### Cambiar un valor especifico de una variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1021,
     "status": "ok",
     "timestamp": 1564562735335,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "23OsvfbXWtel",
    "outputId": "772e669b-cea4-4163-f5c8-b23dc5ccd4a2"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Variable 'UnreadVariable' shape=(2, 3) dtype=float32, numpy=\n",
       "array([[  1.,   2., 100.],\n",
       "       [  4.,   5.,   6.]], dtype=float32)>"
      ]
     },
     "execution_count": 15,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf2_variable[0, 2].assign(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 786,
     "status": "ok",
     "timestamp": 1564562737220,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "cSj0YvJkXZu8",
    "outputId": "b09b1360-878e-495b-ef92-3c7acd543edf"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Variable 'Variable:0' shape=(2, 3) dtype=float32, numpy=\n",
       "array([[  1.,   2., 100.],\n",
       "       [  4.,   5.,   6.]], dtype=float32)>"
      ]
     },
     "execution_count": 16,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf2_variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "QdbG1kvXD2O-"
   },
   "source": [
    "### Operaciones con tensores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1213,
     "status": "ok",
     "timestamp": 1564562751614,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "M8TE6VvuFDXd",
    "outputId": "1471c3ed-5212-46ed-9d65-dae5d945ef7c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: id=27, shape=(2, 2), dtype=int32, numpy=\n",
       "array([[1, 2],\n",
       "       [3, 4]], dtype=int32)>"
      ]
     },
     "execution_count": 17,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor = tf.constant([[1, 2], [3, 4]])\n",
    "tensor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "9AelsMJIFYku"
   },
   "source": [
    "#### Sumar un escalar a un tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 661,
     "status": "ok",
     "timestamp": 1564562763710,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "nBHn9DTVjW6s",
    "outputId": "b0376d01-603b-48c5-b977-0e7c1abac333"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: id=30, shape=(2, 2), dtype=int32, numpy=\n",
       "array([[3, 4],\n",
       "       [5, 6]], dtype=int32)>"
      ]
     },
     "execution_count": 18,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor + 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "oQY7rduwFfEC"
   },
   "source": [
    "#### Multiplicar un escalar por un tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 668,
     "status": "ok",
     "timestamp": 1564562778693,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "WZkzLDnVFBZF",
    "outputId": "1bbbc318-ff7d-4cc2-ecf8-c16a617a7ec0"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: id=33, shape=(2, 2), dtype=int32, numpy=\n",
       "array([[ 5, 10],\n",
       "       [15, 20]], dtype=int32)>"
      ]
     },
     "execution_count": 19,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensor * 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "0algGv7HFrUI"
   },
   "source": [
    "#### Utilizar funciones de Numpy sobre tensores de TensorFlow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1620,
     "status": "ok",
     "timestamp": 1564562809981,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "zTeiyc6HFyIs",
    "outputId": "221e5839-2d16-41f5-f773-87a33ea1a99b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1,  4],\n",
       "       [ 9, 16]], dtype=int32)"
      ]
     },
     "execution_count": 20,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtener los cuadrados de todos los números de un tensor de TensorFlow\n",
    "np.square(tensor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 672,
     "status": "ok",
     "timestamp": 1564562821943,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "zcR_Z_4vF2wG",
    "outputId": "b441c093-f4ce-446e-9c2e-298ac6456304"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 1.41421356],\n",
       "       [1.73205081, 2.        ]])"
      ]
     },
     "execution_count": 21,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtener la raíz cuadrada de todos los números de un tensor de TensorFlow\n",
    "np.sqrt(tensor)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "UL--f1anIMRl"
   },
   "source": [
    "#### Producto escalar entre dos tensores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 670,
     "status": "ok",
     "timestamp": 1564562837421,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "6DGgNB--F6Q1",
    "outputId": "6334bbd7-1e0d-4d99-ae51-485270a70943"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 87, 106],\n",
       "       [197, 216]], dtype=int32)"
      ]
     },
     "execution_count": 22,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    " np.dot(tensor, tensor_20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "12dtWEKjXl7l"
   },
   "source": [
    "### Strings en TensorFlow 2.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 655,
     "status": "ok",
     "timestamp": 1564562846933,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "fXj_Be2bXgdj",
    "outputId": "6217759d-7018-4dcc-fe25-d4fbf3f2689a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: id=41, shape=(), dtype=string, numpy=b'TensorFlow'>"
      ]
     },
     "execution_count": 23,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_string = tf.constant(\"TensorFlow\")\n",
    "tf_string"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "R9VXL59XYPDG"
   },
   "source": [
    "#### Operaciones simples con strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 885,
     "status": "ok",
     "timestamp": 1564562859915,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "_sIYqcC9YjoS",
    "outputId": "0b753dbb-c08a-47f1-f7fc-f8ed62a6fd8c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: id=43, shape=(), dtype=int32, numpy=10>"
      ]
     },
     "execution_count": 24,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.strings.length(tf_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 74
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 855,
     "status": "ok",
     "timestamp": 1564562861877,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "vxQRhILBYmiH",
    "outputId": "fb735d47-0d15-41ef-b266-9302c8424cf8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: id=48, shape=(10,), dtype=int32, numpy=array([ 84, 101, 110, 115, 111, 114,  70, 108, 111, 119], dtype=int32)>"
      ]
     },
     "execution_count": 25,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.strings.unicode_decode(tf_string, \"UTF8\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "tEjJCCK2ZUzT"
   },
   "source": [
    "#### Almacenar arrays de strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "YHvHvS0DZakV"
   },
   "outputs": [],
   "source": [
    "tf_string_array = tf.constant([\"TensorFlow\", \"Deep Learning\", \"AI\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 640,
     "status": "ok",
     "timestamp": 1564562884614,
     "user": {
      "displayName": "Juan Gabriel Gomila Salas",
      "photoUrl": "https://lh4.googleusercontent.com/-RJ38mzk8Fog/AAAAAAAAAAI/AAAAAAAAA_g/VV8PcNMAUrk/s64/photo.jpg",
      "userId": "03106941341701838274"
     },
     "user_tz": -120
    },
    "id": "wyFS4E9uZh21",
    "outputId": "815c31ea-2560-4249-e36a-479a4cad0322"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tf.Tensor(b'TensorFlow', shape=(), dtype=string)\n",
      "tf.Tensor(b'Deep Learning', shape=(), dtype=string)\n",
      "tf.Tensor(b'AI', shape=(), dtype=string)\n"
     ]
    }
   ],
   "source": [
    "# Iterar sobre un array de strings en TF\n",
    "for string in tf_string_array:\n",
    "  print(string)"
   ]
  }
 ],
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   "collapsed_sections": [],
   "name": "Colab 2 - Introducción a TensorFlow 2.0 .ipynb",
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     "timestamp": 1564561930493
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