stable_dreamfusion.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/jstenner/ainotebooks/blob/main/stable_dreamfusion.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rVDV5YJ9Ngdw"
      },
      "source": [
        "# Example usage of [stable-dreamfusion](https://github.com/ashawkey/stable-dreamfusion)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Od2eF2ZwH_6W"
      },
      "source": [
        "### Check the machine"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vfirUQVeMvm8",
        "outputId": "3ae6c33d-5f20-493f-9576-1896d9c33f6d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sun Oct  9 13:51:45 2022       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 460.32.03    Driver Version: 460.32.03    CUDA Version: 11.2     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   45C    P8     9W /  70W |      0MiB / 15109MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "! nvidia-smi"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-HG8OCXSIGLQ"
      },
      "source": [
        "### Setup"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 327,
          "referenced_widgets": [
            "e0df703a222c4122be310aa7d717c921",
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            "899cd1bd374d481cab20e082b34e4606",
            "b4788f4e746b44e290579b133a22d79d",
            "bb2ef5fd131545faa471d194ef5e8778",
            "1919aed5457b445c9eb4d6e9b0854e6e",
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            "4d3deb9d7ce549c7b20ba9355e70846f",
            "0fbb4ef0140f453c9d9a49c15a99073d",
            "7976c2c17ee84ee1921cbf9abf26b241",
            "984857e0d1d1407f943ed61edea3051b"
          ]
        },
        "id": "JWwVGf9NNQnv",
        "outputId": "f3f46abf-9efb-4187-b6bc-241d7e989f5e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Login successful\n",
            "Your token has been saved to /root/.huggingface/token\n"
          ]
        }
      ],
      "source": [
        "#@title login to huggingface to download stable diffusion\n",
        "from huggingface_hub import notebook_login\n",
        "from google.colab import output\n",
        "\n",
        "output.enable_custom_widget_manager()\n",
        "notebook_login()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y-LhllLN-5ph",
        "outputId": "266d92b7-7c89-423c-a615-454968bbcaf1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'stable-dreamfusion'...\n",
            "remote: Enumerating objects: 205, done.\u001b[K\n",
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            "Resolving deltas: 100% (105/105), done.\n",
            "/content/stable-dreamfusion\n",
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            "Installing collected packages: tokenizers, huggingface-hub, commonmark, xatlas, trimesh, transformers, torch-ema, tensorboardX, rich, PyMCubes, ninja, imageio-ffmpeg, diffusers, dearpygui\n",
            "Successfully installed PyMCubes-0.1.2 commonmark-0.9.1 dearpygui-1.7.1 diffusers-0.4.1 huggingface-hub-0.10.0 imageio-ffmpeg-0.4.7 ninja-1.10.2.4 rich-12.6.0 tensorboardX-2.5.1 tokenizers-0.12.1 torch-ema-0.3 transformers-4.22.2 trimesh-3.15.3 xatlas-0.0.6\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting git+https://github.com/NVlabs/nvdiffrast/\n",
            "  Cloning https://github.com/NVlabs/nvdiffrast/ to /tmp/pip-req-build-_v_6ipk1\n",
            "  Running command git clone -q https://github.com/NVlabs/nvdiffrast/ /tmp/pip-req-build-_v_6ipk1\n",
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            "  Building wheel for nvdiffrast (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "  Stored in directory: /tmp/pip-ephem-wheel-cache-l51uneo3/wheels/03/16/0a/c5fbe197e3519adf568dd98719becee0fc7999e1787ffdf688\n",
            "Successfully built nvdiffrast\n",
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            "Successfully installed nvdiffrast-0.3.0\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Processing ./raymarching\n",
            "\u001b[33m  DEPRECATION: A future pip version will change local packages to be built in-place without first copying to a temporary directory. We recommend you use --use-feature=in-tree-build to test your packages with this new behavior before it becomes the default.\n",
            "   pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.\u001b[0m\n",
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            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Processing ./shencoder\n",
            "\u001b[33m  DEPRECATION: A future pip version will change local packages to be built in-place without first copying to a temporary directory. We recommend you use --use-feature=in-tree-build to test your packages with this new behavior before it becomes the default.\n",
            "   pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.\u001b[0m\n",
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            "  Building wheel for shencoder (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for shencoder: filename=shencoder-0.0.0-cp37-cp37m-linux_x86_64.whl size=1164764 sha256=71c7793ea9fc537979327832a208bbb613820c102dadbe457f737e2c1396db8d\n",
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            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Processing ./freqencoder\n",
            "\u001b[33m  DEPRECATION: A future pip version will change local packages to be built in-place without first copying to a temporary directory. We recommend you use --use-feature=in-tree-build to test your packages with this new behavior before it becomes the default.\n",
            "   pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.\u001b[0m\n",
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            "  Building wheel for freqencoder (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for freqencoder: filename=freqencoder-0.0.0-cp37-cp37m-linux_x86_64.whl size=1087748 sha256=188894ae175f747cca2ec3e6f6d6f1b386d238e098c70813b24d9356ad3d7403\n",
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            "Successfully installed freqencoder-0.0.0\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Processing ./gridencoder\n",
            "\u001b[33m  DEPRECATION: A future pip version will change local packages to be built in-place without first copying to a temporary directory. We recommend you use --use-feature=in-tree-build to test your packages with this new behavior before it becomes the default.\n",
            "   pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.\u001b[0m\n",
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            "  Building wheel for gridencoder (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for gridencoder: filename=gridencoder-0.0.0-cp37-cp37m-linux_x86_64.whl size=3600267 sha256=6b5c8a2460509090a6617a9533414b30429b5b8ff733310ded648573d2184507\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-ttligx6r/wheels/c1/2a/0c/080200a51388d425811df50614efdaa01ee9fd45788a19c5f8\n",
            "Successfully built gridencoder\n",
            "Installing collected packages: gridencoder\n",
            "Successfully installed gridencoder-0.0.0\n"
          ]
        }
      ],
      "source": [
        "#@title install dependencies\n",
        "! git clone https://github.com/ashawkey/stable-dreamfusion.git\n",
        "\n",
        "%cd stable-dreamfusion\n",
        "\n",
        "# install requirements\n",
        "! pip install -r requirements.txt\n",
        "! pip install git+https://github.com/NVlabs/nvdiffrast/\n",
        "\n",
        "# install extension modules\n",
        "! bash scripts/install_ext.sh"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VklXFNisIrDo"
      },
      "source": [
        "### Training & Testing\n",
        "* The training already includes exporting video and mesh once finished. So you don't need to run the testing if you wait until the training finishes. But if you interrupt the training, a manual testing is needed.\n",
        "* It takes about 0.7s per training step, so the default 5000 training steps take around 1 hour to finish. A larger `Training_iters` usually leads to better results.\n",
        "* Increasing `Training_nerf_resolution` leads to better rendering quality too, but requires more GPU memory.\n",
        "* If the NeRF fails to learn anything (empty scene, only background), try to decrease `Lambda_entropy` which regularizes the learned opacity."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "M4WGvOBBI1ae",
        "cellView": "form"
      },
      "outputs": [],
      "source": [
        "#@markdown ####**Training Settings:**\n",
        "Prompt_text = \"a DSLR photo of a pineapple\" #@param {type: 'string'}\n",
        "Training_iters = 5000 #@param {type: 'integer'}\n",
        "Learning_rate = 1e-3 #@param {type: 'number'}\n",
        "Training_nerf_resolution = 64  #@param {type: 'integer'}\n",
        "# CUDA_ray = True #@param {type: 'boolean'}\n",
        "# View_dependent_prompt = True #@param {type: 'boolean'}\n",
        "# FP16 = True #@param {type: 'boolean'}\n",
        "Seed = 0 #@param {type: 'integer'}\n",
        "Lambda_entropy = 1e-4 #@param {type: 'number'}\n",
        "Checkpoint = 'scratch' #@param {type: 'string'}\n",
        "\n",
        "#@markdown ---\n",
        "\n",
        "#@markdown ####**Output Settings:**\n",
        "Workspace = \"trial\" #@param{type: 'string'}\n",
        "# Save_mesh = True #@param {type: 'boolean'}\n",
        "\n",
        "# processings\n",
        "Prompt_text = \"'\" + Prompt_text + \"'\""
      ]
    },
    {
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        },
        "id": "XHHjlAkwJDa5",
        "outputId": "13e8709e-eeca-47a1-dbb3-2ff5c910f7be"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Namespace(H=800, O=True, O2=False, W=800, albedo_iters=1000, angle_front=30, angle_overhead=30, backbone='grid', bg_radius=1.4, bound=1, ckpt='scratch', cuda_ray=True, density_thresh=10, dir_text=True, dt_gamma=0, eval_interval=10, fovy=60, fovy_range=[40, 70], fp16=True, gui=False, guidance='stable-diffusion', h=64, iters=5000, jitter_pose=False, lambda_entropy=0.0001, lambda_opacity=0, lambda_orient=0.01, light_phi=0, light_theta=60, lr=0.001, max_ray_batch=4096, max_spp=1, max_steps=1024, min_near=0.1, num_steps=64, radius=3, radius_range=[1.0, 1.5], save_mesh=True, seed=0, test=False, text='a DSLR photo of a pineapple', update_extra_interval=16, upsample_steps=64, w=64, workspace='trial')\n",
            "NeRFNetwork(\n",
            "  (encoder): GridEncoder: input_dim=3 num_levels=16 level_dim=2 resolution=16 -> 2048 per_level_scale=1.3819 params=(6119864, 2) gridtype=tiled align_corners=False\n",
            "  (sigma_net): MLP(\n",
            "    (net): ModuleList(\n",
            "      (0): Linear(in_features=32, out_features=64, bias=True)\n",
            "      (1): Linear(in_features=64, out_features=64, bias=True)\n",
            "      (2): Linear(in_features=64, out_features=4, bias=True)\n",
            "    )\n",
            "  )\n",
            "  (encoder_bg): FreqEncoder: input_dim=3 degree=6 output_dim=39\n",
            "  (bg_net): MLP(\n",
            "    (net): ModuleList(\n",
            "      (0): Linear(in_features=39, out_features=64, bias=True)\n",
            "      (1): Linear(in_features=64, out_features=3, bias=True)\n",
            "    )\n",
            "  )\n",
            ")\n",
            "[INFO] try to load hugging face access token from the default place, make sure you have run `huggingface-cli login`.\n",
            "[INFO] loading stable diffusion...\n"
          ]
        },
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          "output_type": "stream",
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          "text": [
            "[INFO] loaded stable diffusion!\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m[\u001b[0mINFO\u001b[1m]\u001b[0m Trainer: ngp | \u001b[1;36m2022\u001b[0m-\u001b[1;36m10\u001b[0m-09_14-\u001b[1;36m02\u001b[0m-\u001b[1;36m31\u001b[0m | cuda | fp16 | trial\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>INFO<span style=\"font-weight: bold\">]</span> Trainer: ngp | <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2022</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>-09_14-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">02</span>-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31</span> | cuda | fp16 | trial\n",
              "</pre>\n"
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              "\u001b[1m[\u001b[0mINFO\u001b[1m]\u001b[0m #parameters: \u001b[1;36m12249015\u001b[0m\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>INFO<span style=\"font-weight: bold\">]</span> #parameters: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12249015</span>\n",
              "</pre>\n"
            ]
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          "metadata": {}
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            "text/plain": [
              "\u001b[1m[\u001b[0mINFO\u001b[1m]\u001b[0m Training from scratch \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>INFO<span style=\"font-weight: bold\">]</span> Training from scratch <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
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            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m1\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.010000\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.010000</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0000 (0.0000): : 100% 100/100 [01:04<00:00,  1.55it/s]\n"
          ]
        },
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            "text/plain": [
              "==> Finished Epoch \u001b[1;36m1\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>.\n",
              "</pre>\n"
            ]
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            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m2\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009991\u001b[0m \u001b[33m...\u001b[0m\n"
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            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009991</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
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        {
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          "text": [
            "loss=0.0000 (0.0000): : 100% 100/100 [01:03<00:00,  1.57it/s]\n"
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            "text/plain": [
              "==> Finished Epoch \u001b[1;36m2\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>.\n",
              "</pre>\n"
            ]
          },
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          "data": {
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              "==> Start Training trial Epoch \u001b[1;36m3\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009982\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009982</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
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          "text": [
            "loss=0.0000 (0.0000): : 100% 100/100 [01:03<00:00,  1.57it/s]\n"
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              "==> Finished Epoch \u001b[1;36m3\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m4\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009972\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009972</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
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          "text": [
            "loss=0.0000 (0.0000): : 100% 100/100 [01:03<00:00,  1.57it/s]\n"
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        {
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              "==> Finished Epoch \u001b[1;36m4\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m5\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009963\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009963</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
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        {
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          "name": "stderr",
          "text": [
            "loss=0.0000 (0.0000): : 100% 100/100 [01:03<00:00,  1.57it/s]\n"
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        {
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              "==> Finished Epoch \u001b[1;36m5\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">5</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m6\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009954\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009954</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
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        {
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          "name": "stderr",
          "text": [
            "loss=0.0000 (0.0000): : 100% 100/100 [01:04<00:00,  1.56it/s]\n"
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        {
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              "==> Finished Epoch \u001b[1;36m6\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">6</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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        {
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          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m7\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009945\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009945</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
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        },
        {
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          "name": "stderr",
          "text": [
            "loss=0.0000 (0.0000): : 100% 100/100 [01:04<00:00,  1.56it/s]\n"
          ]
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        {
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              "==> Finished Epoch \u001b[1;36m7\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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        {
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          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m8\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009936\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009936</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
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        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0000 (0.0000): : 100% 100/100 [01:04<00:00,  1.55it/s]\n"
          ]
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        {
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              "==> Finished Epoch \u001b[1;36m8\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">8</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
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          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m9\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009927\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009927</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0000 (0.0000): : 100% 100/100 [01:04<00:00,  1.56it/s]\n"
          ]
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        {
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              "==> Finished Epoch \u001b[1;36m9\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
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          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m10\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009917\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009917</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
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        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0000 (0.0000): : 100% 100/100 [01:04<00:00,  1.55it/s]\n"
          ]
        },
        {
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              "==> Finished Epoch \u001b[1;36m10\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "++> Evaluate trial at epoch \u001b[1;36m10\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">++&gt; Evaluate trial at epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0000 (0.0000): : 100% 5/5 [00:02<00:00,  1.75it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "++> Evaluate epoch \u001b[1;36m10\u001b[0m Finished.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">++&gt; Evaluate epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">10</span> Finished.\n",
              "</pre>\n"
            ]
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          "data": {
            "text/plain": [
              "\u001b[1m[\u001b[0mINFO\u001b[1m]\u001b[0m New best result: \u001b[3;35mNone\u001b[0m --> \u001b[1;36m2.548681186453905e-05\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>INFO<span style=\"font-weight: bold\">]</span> New best result: <span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span> --&gt; <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.548681186453905e-05</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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        {
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          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m11\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009908\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009908</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
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          "metadata": {}
        },
        {
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          "name": "stderr",
          "text": [
            "loss=0.0016 (0.0013): : 100% 100/100 [01:23<00:00,  1.19it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m11\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">11</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m12\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009899\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009899</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0015 (0.0012): : 100% 100/100 [01:22<00:00,  1.21it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m12\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">12</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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        {
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          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m13\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009890\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009890</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0013 (0.0012): : 100% 100/100 [01:24<00:00,  1.19it/s]\n"
          ]
        },
        {
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          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m13\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">13</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m14\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009881\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009881</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0013 (0.0011): : 100% 100/100 [01:21<00:00,  1.23it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m14\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">14</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m15\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009872\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009872</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0013 (0.0011): : 100% 100/100 [01:19<00:00,  1.25it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m15\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">15</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m16\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009863\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009863</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0000 (0.0010): : 100% 100/100 [01:17<00:00,  1.29it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m16\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">16</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m17\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009854\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009854</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0013 (0.0011): : 100% 100/100 [01:17<00:00,  1.28it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m17\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">17</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m18\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009845\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009845</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0013 (0.0012): : 100% 100/100 [01:18<00:00,  1.28it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m18\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">18</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m19\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009836\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009836</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0012 (0.0011): : 100% 100/100 [01:16<00:00,  1.31it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m19\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">19</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m20\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009827\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009827</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0015 (0.0011): : 100% 100/100 [01:15<00:00,  1.33it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m20\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "++> Evaluate trial at epoch \u001b[1;36m20\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">++&gt; Evaluate trial at epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0000 (0.0000): : 100% 5/5 [00:01<00:00,  2.79it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "++> Evaluate epoch \u001b[1;36m20\u001b[0m Finished.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">++&gt; Evaluate epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">20</span> Finished.\n",
              "</pre>\n"
            ]
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m[\u001b[0mINFO\u001b[1m]\u001b[0m New best result: \u001b[1;36m2.548681186453905e-05\u001b[0m --> \u001b[1;36m1.715841681289021e-05\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>INFO<span style=\"font-weight: bold\">]</span> New best result: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.548681186453905e-05</span> --&gt; <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.715841681289021e-05</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m21\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009817\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">21</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009817</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0013 (0.0011): : 100% 100/100 [01:15<00:00,  1.33it/s]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Finished Epoch \u001b[1;36m21\u001b[0m.\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Finished Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">21</span>.\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "==> Start Training trial Epoch \u001b[1;36m22\u001b[0m, \u001b[33mlr\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.009808\u001b[0m \u001b[33m...\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">==&gt; Start Training trial Epoch <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">22</span>, <span style=\"color: #808000; text-decoration-color: #808000\">lr</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.009808</span> <span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loss=0.0014 (0.0012): :  13% 13/100 [00:09<01:05,  1.32it/s]"
          ]
        }
      ],
      "source": [
        "#@title start training\n",
        "%run main.py -O --text {Prompt_text} --workspace {Workspace} --iters {Training_iters} --lr {Learning_rate} --w {Training_nerf_resolution} --h {Training_nerf_resolution} --seed {Seed} --lambda_entropy {Lambda_entropy} --ckpt {Checkpoint} --save_mesh"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "BJ6-1tkaRTpy"
      },
      "outputs": [],
      "source": [
        "#@markdown ####**Testing Settings:**\n",
        "\n",
        "Workspace_test = \"trial\" #@param{type: 'string'}\n",
        "# Save_mesh = True #@param {type: 'boolean'}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6liVfcPZRGWD"
      },
      "outputs": [],
      "source": [
        "#@title (optional) testing \n",
        "%run main.py -O --test --workspace {Workspace_test} --save_mesh"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VxzEhYT5PQIV"
      },
      "source": [
        "### Display results\n",
        "* RGB and Depth video are located at `{Workspace}/results/*.mp4`\n",
        "* Mesh is under `{Workspace}/mesh/`, you could see three files named `mesh.obj`, `mesh.mtl`, and `albedo.png`."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lmmiVeUDOXI6"
      },
      "outputs": [],
      "source": [
        "#@title display RGB video\n",
        "import os\n",
        "import glob\n",
        "from IPython.display import HTML\n",
        "from base64 import b64encode\n",
        "\n",
        "def get_latest_file(path):\n",
        "  dir_list = glob.glob(path)\n",
        "  dir_list.sort(key=lambda x: os.path.getmtime(x))\n",
        "  return dir_list[-1]\n",
        "\n",
        "def show_video(video_path, video_width = 600):\n",
        "   \n",
        "  video_file = open(video_path, \"r+b\").read()\n",
        "  video_url = f\"data:video/mp4;base64,{b64encode(video_file).decode()}\"\n",
        "\n",
        "  return HTML(f\"\"\"<video width={video_width} controls><source src=\"{video_url}\"></video>\"\"\")\n",
        " \n",
        "rgb_video = get_latest_file(os.path.join(Workspace, 'results', '*_rgb.mp4'))\n",
        "show_video(rgb_video)"
      ]
    }
  ],
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