hybridvae_classifier_mnist.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "vae_classifier_mnist_v4.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU",
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "64eb0428349d4b09897c97b859268803": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_bbb0602028fc4404adb73d12e431aef5",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_0bb62325f92f4f73b2c9c76a919a9c59",
              "IPY_MODEL_bd30c0b1dab34e368782f4bd90e0ed9e"
            ]
          }
        },
        "bbb0602028fc4404adb73d12e431aef5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "0bb62325f92f4f73b2c9c76a919a9c59": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_567a758d520640d28558babca2e02fb4",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_c6416baf273b4ace83de9f2d1aa870d6"
          }
        },
        "bd30c0b1dab34e368782f4bd90e0ed9e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_38407d90965f4ac2bbe205bf287c17ff",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 9920512/? [00:02&lt;00:00, 4049869.12it/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_0f785e7ea926487e869d4216cbb4e674"
          }
        },
        "567a758d520640d28558babca2e02fb4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "c6416baf273b4ace83de9f2d1aa870d6": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "38407d90965f4ac2bbe205bf287c17ff": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "0f785e7ea926487e869d4216cbb4e674": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "964a1a2e88d74cb99813af7b23f3dbd1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_1ebc9758c2b64d1086614da432bbf89c",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_968706e594994791a711cad4eb75fb2a",
              "IPY_MODEL_3c47f68e359a4894b307bd94285b13fb"
            ]
          }
        },
        "1ebc9758c2b64d1086614da432bbf89c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "968706e594994791a711cad4eb75fb2a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_755f1f55ef494819be1e58f8f3cd4ca7",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_95bffa58e01949df8e85bfd99fbd26fc"
          }
        },
        "3c47f68e359a4894b307bd94285b13fb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_e64706bf40fc48568827541070af84db",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 32768/? [00:01&lt;00:00, 32597.17it/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_8c162119c481469db206035e0ce39acc"
          }
        },
        "755f1f55ef494819be1e58f8f3cd4ca7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "95bffa58e01949df8e85bfd99fbd26fc": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "e64706bf40fc48568827541070af84db": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "8c162119c481469db206035e0ce39acc": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "3f6a7959fa6a402e86c0f60de6433939": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_1b61310ab1884e4bb98153abb1678554",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_309368ee40234756ac9f44afc2f58cbf",
              "IPY_MODEL_4af1b3061df44b24877b5470d187cdfc"
            ]
          }
        },
        "1b61310ab1884e4bb98153abb1678554": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "309368ee40234756ac9f44afc2f58cbf": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_0fd6f4d3f2094184870a47e5fb9199f9",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_226f173545f94cb1969494621315854b"
          }
        },
        "4af1b3061df44b24877b5470d187cdfc": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_d269b221ed0f4a78961e1f7b2de4fd53",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 1654784/? [00:00&lt;00:00, 2233556.43it/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_95a2bed29e514ff286f8722ae496549f"
          }
        },
        "0fd6f4d3f2094184870a47e5fb9199f9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "226f173545f94cb1969494621315854b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "d269b221ed0f4a78961e1f7b2de4fd53": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "95a2bed29e514ff286f8722ae496549f": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "9b45e948310f445c9e7e6533dec7d95b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_9b76330593514c5d9e9bfb4e0bd5493b",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_8f002ea82ab942429d657ffeec8f8563",
              "IPY_MODEL_e01efa24bf114f2d8d6a7a76c80d3ef0"
            ]
          }
        },
        "9b76330593514c5d9e9bfb4e0bd5493b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "8f002ea82ab942429d657ffeec8f8563": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_d8b5d6557e7843e0a58b320cf46e3524",
            "_dom_classes": [],
            "description": "  0%",
            "_model_name": "FloatProgressModel",
            "bar_style": "info",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 0,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_f16db7bc073440a7a7d1688c848e50a9"
          }
        },
        "e01efa24bf114f2d8d6a7a76c80d3ef0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_10285dae20284c09814c0d29dc58dca7",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 0/4542 [00:00&lt;?, ?it/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_bca66975fc0648628b1ef7a1e6a434aa"
          }
        },
        "d8b5d6557e7843e0a58b320cf46e3524": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "f16db7bc073440a7a7d1688c848e50a9": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "10285dae20284c09814c0d29dc58dca7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "bca66975fc0648628b1ef7a1e6a434aa": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "6wEqGHMZtJl-"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "import torch \n",
        "from torch.autograd import Variable\n",
        "import torch.nn as nn\n",
        "from torch.nn import Conv2d, InstanceNorm2d, ConvTranspose2d\n",
        "from torch import optim \n",
        "import torch.nn.functional as F \n",
        "import torchvision"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iDHyAlu4trKZ"
      },
      "source": [
        "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pV9vimYctv9v",
        "outputId": "9ab21c51-953c-4ca3-932e-972f1818ff3e"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/gdrive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dYMHmtg8twjR"
      },
      "source": [
        "# this won't work if the drive is shared with you\n",
        "# solution: right click on the shared  project folder and select 'add shortcut to my drive'\n",
        "%cd gdrive/My\\ Drive/CS7643_Final_Project"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mqG9RaDIvpV9"
      },
      "source": [
        "class VAE_Classifier(nn.Module):\n",
        "  def __init__(self, latent_dim = 20):\n",
        "    super(VAE_Classifier, self).__init__()\n",
        "    self.latent_dim = latent_dim\n",
        "\n",
        "    self.cn1 = nn.Conv2d(1, 32, kernel_size = 3, stride = 2, padding = 1)\n",
        "    self.cn2 = nn.Conv2d(32, 64, kernel_size = 3, stride = 2, padding = 1)\n",
        "    self.m = nn.Linear(64 * 7 * 7, latent_dim)\n",
        "    self.v = nn.Linear(64 * 7 * 7, latent_dim)\n",
        "\n",
        "    self.fc1 = nn.Linear(latent_dim, 40)\n",
        "    self.fc2 = nn.Linear(40, 40)\n",
        "    self.fc3 = nn.Linear(40, 30)\n",
        "    self.fc4 = nn.Linear(30, 20)\n",
        "    self.fc5 = nn.Linear(20, 10)\n",
        "\n",
        "  def encode(self, x):\n",
        "    x = F.relu(self.cn1(x))\n",
        "    x = F.relu(self.cn2(x))\n",
        "    x = x.view(x.shape[0], -1)\n",
        "  \n",
        "    mu = F.relu(self.m(x))\n",
        "    logvar = F.relu(self.v(x))\n",
        "    return mu, logvar\n",
        "  \n",
        "  def decode(self, z):\n",
        "    out = F.relu(self.fc1(z))\n",
        "    out = F.relu(self.fc2(out))\n",
        "    out = F.relu(self.fc3(out))\n",
        "    out = F.relu(self.fc4(out))\n",
        "    out = self.fc5(out)\n",
        "    return out\n",
        "  \n",
        "  def reparameterize(self, mu, logvar):\n",
        "    std = torch.exp(0.5*logvar)\n",
        "    eps = torch.randn_like(std)\n",
        "    return mu + eps*std\n",
        "  \n",
        "  def forward(self, x):\n",
        "    mu, logvar = self.encode(x)\n",
        "    lz = self.reparameterize(mu, logvar)\n",
        "    out = self.decode(lz)\n",
        "    return out, mu, logvar"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PABVTH4rg9bR"
      },
      "source": [
        "def loss_function(pred, label, mu, logvar):\n",
        "  crossentropy = nn.CrossEntropyLoss()\n",
        "  \n",
        "  CE = crossentropy(pred, label)\n",
        "  KLD = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp())\n",
        "  return CE + KLD"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ahjR_IKy6Chh"
      },
      "source": [
        "def evaluate_model(model, dataloader, criterion = nn.CrossEntropyLoss()):\n",
        "    \"\"\"\n",
        "    Calculates the average loss and accuracy of the model on a dataset\n",
        "    \"\"\"\n",
        "    model.eval() # Notify all layers we're in eval mode instead of training mode\n",
        "    loss, total, correct = 0, 0, 0\n",
        "    n = 0\n",
        "    with torch.no_grad():\n",
        "      for xs, ys in dataloader:\n",
        "          output, _, _ = model(xs.to(device))\n",
        "          loss += criterion(output, ys.to(device)).item()\n",
        "          _, predictions = torch.max(output.data, 1)\n",
        "          total += ys.size(0)\n",
        "          correct += (predictions == ys.to(device)).sum().item()\n",
        "          n += 1\n",
        "    \n",
        "    print(f'\\nTest loss: {loss / n: .2f} | Test accuracy: {correct / total : .2f}')\n",
        "    return loss / n, 100 * correct / total"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w7uwln3qtTip"
      },
      "source": [
        "batch_size = 128"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qT2yN-Z3vTfy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426,
          "referenced_widgets": [
            "64eb0428349d4b09897c97b859268803",
            "bbb0602028fc4404adb73d12e431aef5",
            "0bb62325f92f4f73b2c9c76a919a9c59",
            "bd30c0b1dab34e368782f4bd90e0ed9e",
            "567a758d520640d28558babca2e02fb4",
            "c6416baf273b4ace83de9f2d1aa870d6",
            "38407d90965f4ac2bbe205bf287c17ff",
            "0f785e7ea926487e869d4216cbb4e674",
            "964a1a2e88d74cb99813af7b23f3dbd1",
            "1ebc9758c2b64d1086614da432bbf89c",
            "968706e594994791a711cad4eb75fb2a",
            "3c47f68e359a4894b307bd94285b13fb",
            "755f1f55ef494819be1e58f8f3cd4ca7",
            "95bffa58e01949df8e85bfd99fbd26fc",
            "e64706bf40fc48568827541070af84db",
            "8c162119c481469db206035e0ce39acc",
            "3f6a7959fa6a402e86c0f60de6433939",
            "1b61310ab1884e4bb98153abb1678554",
            "309368ee40234756ac9f44afc2f58cbf",
            "4af1b3061df44b24877b5470d187cdfc",
            "0fd6f4d3f2094184870a47e5fb9199f9",
            "226f173545f94cb1969494621315854b",
            "d269b221ed0f4a78961e1f7b2de4fd53",
            "95a2bed29e514ff286f8722ae496549f",
            "9b45e948310f445c9e7e6533dec7d95b",
            "9b76330593514c5d9e9bfb4e0bd5493b",
            "8f002ea82ab942429d657ffeec8f8563",
            "e01efa24bf114f2d8d6a7a76c80d3ef0",
            "d8b5d6557e7843e0a58b320cf46e3524",
            "f16db7bc073440a7a7d1688c848e50a9",
            "10285dae20284c09814c0d29dc58dca7",
            "bca66975fc0648628b1ef7a1e6a434aa"
          ]
        },
        "outputId": "f73d8057-5eb3-4c2a-9886-3e7d2af180a6"
      },
      "source": [
        "train_data_loader = torch.utils.data.DataLoader(\n",
        "  torchvision.datasets.MNIST('/files/', train=True, download=True,\n",
        "                             transform=torchvision.transforms.Compose([\n",
        "                               torchvision.transforms.ToTensor(),\n",
        "                               torchvision.transforms.Normalize(\n",
        "                                 (0.1307,), (0.3081,))\n",
        "                             ])),\n",
        "  batch_size=batch_size, shuffle=True)\n",
        "\n",
        "test_data_loader = torch.utils.data.DataLoader(\n",
        "  torchvision.datasets.MNIST('/files/', train=False, download=True,\n",
        "                             transform=torchvision.transforms.Compose([\n",
        "                               torchvision.transforms.ToTensor(),\n",
        "                               torchvision.transforms.Normalize(\n",
        "                                 (0.1307,), (0.3081,))\n",
        "                             ])),\n",
        "  batch_size=batch_size, shuffle=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to /files/MNIST/raw/train-images-idx3-ubyte.gz\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "64eb0428349d4b09897c97b859268803",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Extracting /files/MNIST/raw/train-images-idx3-ubyte.gz to /files/MNIST/raw\n",
            "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz to /files/MNIST/raw/train-labels-idx1-ubyte.gz\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "964a1a2e88d74cb99813af7b23f3dbd1",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Extracting /files/MNIST/raw/train-labels-idx1-ubyte.gz to /files/MNIST/raw\n",
            "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz to /files/MNIST/raw/t10k-images-idx3-ubyte.gz\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3f6a7959fa6a402e86c0f60de6433939",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Extracting /files/MNIST/raw/t10k-images-idx3-ubyte.gz to /files/MNIST/raw\n",
            "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to /files/MNIST/raw/t10k-labels-idx1-ubyte.gz\n",
            "\n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "9b45e948310f445c9e7e6533dec7d95b",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Extracting /files/MNIST/raw/t10k-labels-idx1-ubyte.gz to /files/MNIST/raw\n",
            "Processing...\n",
            "Done!\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/torchvision/datasets/mnist.py:480: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at  /pytorch/torch/csrc/utils/tensor_numpy.cpp:141.)\n",
            "  return torch.from_numpy(parsed.astype(m[2], copy=False)).view(*s)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jclyOocJ1xCS"
      },
      "source": [
        "log_epoch = 10"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "68cCAxge0fP_"
      },
      "source": [
        "classifier = VAE_Classifier().to(device)\n",
        "optimizer = optim.Adam(params = classifier.parameters())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "334Pk98r3Rjw"
      },
      "source": [
        "losses = []\n",
        "test_losses = []\n",
        "epochs = 200"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "LyCXxlFH1HYm",
        "outputId": "5edc3601-5de7-4194-9e02-7c5f9284ba68"
      },
      "source": [
        "for epoch in range(1, epochs + 1):\n",
        "  total = 0\n",
        "  n = 0\n",
        "  for x, y in train_data_loader:\n",
        "\n",
        "    optimizer.zero_grad()\n",
        "    \n",
        "    out, mu, logvar = classifier(x.to(device))\n",
        "    loss = loss_function(out, y.to(device), mu, logvar)\n",
        "    loss.backward()\n",
        "    optimizer.step()\n",
        "\n",
        "    total += loss.item()\n",
        "    n += 1\n",
        "  \n",
        "  losses.append(total / n)\n",
        "  test_loss, test_accuracy = evaluate_model(classifier, test_data_loader)\n",
        "  # put model back in train mode after putting it in eval mode\n",
        "  classifier.train()\n",
        "  test_losses.append(test_loss)\n",
        "  \n",
        "  print('Epoch: {}, Avg Loss: {:.4f}'.format(epoch, total / n))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 1, Avg Loss: 2.3136\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 2, Avg Loss: 2.3016\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 3, Avg Loss: 2.3015\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 4, Avg Loss: 2.3015\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 5, Avg Loss: 2.3015\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 6, Avg Loss: 2.3015\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 7, Avg Loss: 2.3014\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 8, Avg Loss: 2.3014\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 9, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 10, Avg Loss: 2.3014\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 11, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 12, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 13, Avg Loss: 2.3014\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 14, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 15, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 16, Avg Loss: 2.3014\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 17, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 18, Avg Loss: 2.3014\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 19, Avg Loss: 2.3014\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 20, Avg Loss: 2.3014\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 21, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 22, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 23, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 24, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 25, Avg Loss: 2.3014\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 26, Avg Loss: 2.3014\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 27, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 28, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 29, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 30, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 31, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 32, Avg Loss: 2.3012\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 33, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 34, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 35, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 36, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 37, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 38, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 39, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 40, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 41, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 42, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 43, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 44, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 45, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 46, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 47, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 48, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 49, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 50, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 51, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 52, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 53, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 54, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 55, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 56, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 57, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 58, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 59, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 60, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 61, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 62, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 63, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 64, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 65, Avg Loss: 2.3013\n",
            "\n",
            "Test loss:  2.30 | Test accuracy:  0.11\n",
            "Epoch: 66, Avg Loss: 2.3013\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-47-2948ed0ee2d6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      8\u001b[0m     \u001b[0mout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmu\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlogvar\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclassifier\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevice\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      9\u001b[0m     \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mloss_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmu\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlogvar\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m     \u001b[0mloss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackward\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[1;32m     11\u001b[0m     \u001b[0moptimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\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     12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/tensor.py\u001b[0m in \u001b[0;36mbackward\u001b[0;34m(self, gradient, retain_graph, create_graph)\u001b[0m\n\u001b[1;32m    219\u001b[0m                 \u001b[0mretain_graph\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mretain_graph\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    220\u001b[0m                 create_graph=create_graph)\n\u001b[0;32m--> 221\u001b[0;31m         \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mautograd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgradient\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mretain_graph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcreate_graph\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    222\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    223\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mregister_hook\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhook\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[0;32m/usr/local/lib/python3.6/dist-packages/torch/autograd/__init__.py\u001b[0m in \u001b[0;36mbackward\u001b[0;34m(tensors, grad_tensors, retain_graph, create_graph, grad_variables)\u001b[0m\n\u001b[1;32m    130\u001b[0m     Variable._execution_engine.run_backward(\n\u001b[1;32m    131\u001b[0m         \u001b[0mtensors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrad_tensors_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mretain_graph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcreate_graph\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 132\u001b[0;31m         allow_unreachable=True)  # allow_unreachable flag\n\u001b[0m\u001b[1;32m    133\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ]
    }
  ]
}