keras_gan_testing.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "keras-gan-testing",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyP6qyID86oYHPruRgdY8cNq",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ayulockin/deepgenerativemodeling/blob/master/keras_gan_testing.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_S6Kx3qbyu9G",
        "colab_type": "code",
        "outputId": "2109b9e7-03c5-42ee-a195-c4fcd080e05a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 146
        }
      },
      "source": [
        "!git clone https://github.com/ayulockin/keras-gan"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'keras-gan'...\n",
            "remote: Enumerating objects: 16, done.\u001b[K\n",
            "remote: Counting objects:   6% (1/16)\u001b[K\rremote: Counting objects:  12% (2/16)\u001b[K\rremote: Counting objects:  18% (3/16)\u001b[K\rremote: Counting objects:  25% (4/16)\u001b[K\rremote: Counting objects:  31% (5/16)\u001b[K\rremote: Counting objects:  37% (6/16)\u001b[K\rremote: Counting objects:  43% (7/16)\u001b[K\rremote: Counting objects:  50% (8/16)\u001b[K\rremote: Counting objects:  56% (9/16)\u001b[K\rremote: Counting objects:  62% (10/16)\u001b[K\rremote: Counting objects:  68% (11/16)\u001b[K\rremote: Counting objects:  75% (12/16)\u001b[K\rremote: Counting objects:  81% (13/16)\u001b[K\rremote: Counting objects:  87% (14/16)\u001b[K\rremote: Counting objects:  93% (15/16)\u001b[K\rremote: Counting objects: 100% (16/16)\u001b[K\rremote: Counting objects: 100% (16/16), done.\u001b[K\n",
            "remote: Compressing objects: 100% (11/11), done.\u001b[K\n",
            "remote: Total 3497 (delta 5), reused 15 (delta 5), pack-reused 3481\u001b[K\n",
            "Receiving objects: 100% (3497/3497), 88.41 MiB | 11.88 MiB/s, done.\n",
            "Resolving deltas: 100% (567/567), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8nNzdq-_1PQs",
        "colab_type": "code",
        "outputId": "f912cc38-7a1a-4eb0-e3d7-0d755de6bd95",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "%cd keras-gan"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/keras-gan\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NOPcT2IFD2I2",
        "colab_type": "code",
        "outputId": "aa5f5206-2b0f-4841-cf2c-a98e34b095fd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "%cd dcgan"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/keras-gan/dcgan\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l3gUsBNbvvKt",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "%%capture\n",
        "!pip install wandb"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BdAl-BWoECTd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "%run -i 'dcgan.py' --entity ayush-thakur --project keras-gan --latentdim 100 --epochs 1500"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}