Tf_forum_14747.ipynb

tf_forum_14747.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyPr1Kv2L3EkMR1w4zcbePvq",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/kiransair/bc280bd2030f8f30feaeb733f1084168/tf_forum_14747.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import tensorflow as tf"
      ],
      "metadata": {
        "id": "N2cNtwQsXm8r"
      },
      "execution_count": 64,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import tensorflow_probability as tfp\n",
        "tfd = tfp.distributions"
      ],
      "metadata": {
        "id": "QBnfHMVzRisy"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mlp2 = tf.keras.Sequential()\n",
        "\n",
        "mlp2.add(tf.keras.Input(shape=(1,)))\n",
        "\n",
        "mlp2.add(tf.keras.layers.Dense(20))\n",
        "\n",
        "mlp2.add(tf.keras.layers.Dense(20))\n",
        "\n",
        "mlp2.add(tf.keras.layers.Dense(1))"
      ],
      "metadata": {
        "id": "IgLIU9s5Rcrd"
      },
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mlp2.get_weights()[0].shape  #1st dense layer"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "egEW14aoS8VW",
        "outputId": "788f7da4-58f7-4f8b-cd0e-3c11ef46ee56"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1, 20)"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mlp2.get_weights()[2].shape  #2nd dense layer"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jaI7d6MrTTEH",
        "outputId": "26961c61-4c71-4e4e-b451-91530459cfd6"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20, 20)"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mlp2.get_weights()[4].shape   #3rd dense layer"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YK8MffxuTZvN",
        "outputId": "d8e7f9bb-6ce4-43af-c368-706eba66dc10"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20, 1)"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "a=np.array([1,])"
      ],
      "metadata": {
        "id": "kj72pFE4SWMG"
      },
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mlp2(a).ndim"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5ONpd4mWRylK",
        "outputId": "c2ffea4b-2f60-45ed-da1a-9bdad99bca50"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2"
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "b=tf.random.normal((20,1))"
      ],
      "metadata": {
        "id": "gGqLyXeeU-D6"
      },
      "execution_count": 65,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a*b.ndim"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tChzOlnoZEI-",
        "outputId": "1d3e87cf-a5b4-4556-da50-8d5ad74dba6f"
      },
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2])"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "mv29EtHBZGZJ"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}