{
 "nbformat": 4,
 "nbformat_minor": 0,
 "metadata": {
  "colab": {
   "name": "Cycle GAN",
   "provenance": [],
   "collapsed_sections": [],
   "toc_visible": true
  },
  "kernelspec": {
   "name": "python3",
   "language": "python",
   "display_name": "Python 3"
  },
  "accelerator": "GPU"
 },
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AYV_dMVDxyc2"
   },
   "source": [
    "[![Github](https://img.shields.io/github/stars/labmlai/annotated_deep_learning_paper_implementations?style=social)](https://github.com/labmlai/annotated_deep_learning_paper_implementations)\n",
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/labmlai/annotated_deep_learning_paper_implementations/blob/master/labml_nn/gan/wasserstein/experiment.ipynb)\n",
    "\n",
    "## DCGAN\n",
    "\n",
    "This is an experiment training DCGAN model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AahG_i2y5tY9"
   },
   "source": [
    "Install the `labml-nn` package"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "ZCzmCrAIVg0L",
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "outputId": "2fe2685f-731c-4c47-854e-a4f00e485281"
   },
   "source": [
    "!pip install labml-nn"
   ],
   "outputs": [],
   "execution_count": null
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SE2VUQ6L5zxI"
   },
   "source": [
    "Imports"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "0hJXx_g0wS2C"
   },
   "source": [
    "\n",
    "from labml import experiment\n",
    "from labml_nn.gan.wasserstein.experiment import Configs"
   ],
   "outputs": [],
   "execution_count": null
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Lpggo0wM6qb-"
   },
   "source": [
    "Create an experiment"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "bFcr9k-l4cAg"
   },
   "source": [
    "experiment.create(name=\"mnist_wgan\")"
   ],
   "outputs": [],
   "execution_count": null
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-OnHLi626tJt"
   },
   "source": [
    "Initialize configurations"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "Piz0c5f44hRo"
   },
   "source": [
    "conf = Configs()"
   ],
   "outputs": [],
   "execution_count": null
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wwMzCqpD6vkL"
   },
   "source": [
    "Set experiment configurations and assign a configurations dictionary to override configurations"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 17
    },
    "id": "e6hmQhTw4nks",
    "outputId": "4be767af-0ebd-4c35-8da0-0e532495e037"
   },
   "source": [
    "experiment.configs(conf,\n",
    "                   {\n",
    "                       'discriminator': 'cnn',\n",
    "                       'generator': 'cnn',\n",
    "                       'label_smoothing': 0.01,\n",
    "                       'generator_loss': 'wasserstein',\n",
    "                       'discriminator_loss': 'wasserstein',\n",
    "                   })"
   ],
   "outputs": [],
   "execution_count": null
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "KJZRf8527GxL"
   },
   "source": [
    "Start the experiment and run the training loop."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 649
    },
    "id": "aIAWo7Fw5DR8",
    "outputId": "e3b02247-8ff9-47b5-8f52-49c9e3b8377f"
   },
   "source": [
    "with experiment.start():\n",
    "    conf.run()"
   ],
   "outputs": [],
   "execution_count": null
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "oBXXlP2b7XZO"
   },
   "source": [
    ""
   ],
   "outputs": [],
   "execution_count": null
  }
 ]
}