GH-2063

GH-2063.ipynb

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      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/gist/ariG23498/dd5c0449166beac5e2bb68a11809d1a3/scratchpad.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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        "outputId": "5ee0baaf-c73f-4db1-ec2d-036a8a6edede"
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      "source": [
        "! pip install -qqq wandb\n",
        "! pip install -qqq pytorch-lightning"
      ],
      "execution_count": 1,
      "outputs": [
        {
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            "\u001b[?25h  Building wheel for subprocess32 (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for pathtools (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[?25h  Building wheel for future (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for PyYAML (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
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      "cell_type": "code",
      "metadata": {
        "id": "8qsTB5TYv6KO"
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      "source": [
        "# Weights & Biases\n",
        "import wandb\n",
        "from pytorch_lightning.loggers import WandbLogger\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
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      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "JuMC1CbZ22uZ",
        "outputId": "c870ef82-104f-419e-bb9a-2cb0adec19e4"
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      "source": [
        "wandb_logger = WandbLogger(project='GH-2063',\n",
        "                           entity=\"repro\",\n",
        "                           name=\"baseline\",\n",
        "                           notes=\"Do as done in the Github\")\n",
        "\n",
        "fig = plt.figure()\n",
        "\n",
        "wandb_logger.experiment.log({'examples': [fig]})"
      ],
      "execution_count": 3,
      "outputs": [
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              "                newScript.onload = resolve;\n",
              "                document.body.appendChild(newScript);\n",
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              "            });\n",
              "            }\n",
              "            loadScript(\"https://cdn.jsdelivr.net/npm/postmate/build/postmate.min.js\").then(() => {\n",
              "            const iframe = document.createElement('iframe')\n",
              "            iframe.style.cssText = \"width:0;height:0;border:none\"\n",
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              "                container: iframe,\n",
              "                url: 'https://wandb.ai/authorize'\n",
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          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n"
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              "\n",
              "                Tracking run with wandb version 0.10.26<br/>\n",
              "                Syncing run <strong style=\"color:#cdcd00\">baseline</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
              "                Project page: <a href=\"https://wandb.ai/repro/GH-2063\" target=\"_blank\">https://wandb.ai/repro/GH-2063</a><br/>\n",
              "                Run page: <a href=\"https://wandb.ai/repro/GH-2063/runs/t3yt8qgy\" target=\"_blank\">https://wandb.ai/repro/GH-2063/runs/t3yt8qgy</a><br/>\n",
              "                Run data is saved locally in <code>/content/wandb/run-20210414_054253-t3yt8qgy</code><br/><br/>\n",
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            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\u001b[0m in \u001b[0;36mlog\u001b[0;34m(self, data, step, commit, sync)\u001b[0m\n\u001b[1;32m   1053\u001b[0m             \u001b[0mcommit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1054\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcommit\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1055\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_row_add\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\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   1056\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1057\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_row_update\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\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/python3.7/dist-packages/wandb/sdk/wandb_history.py\u001b[0m in \u001b[0;36m_row_add\u001b[0;34m(self, row)\u001b[0m\n\u001b[1;32m     42\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_row_add\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrow\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     43\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 44\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_flush\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     45\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_step\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     46\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_history.py\u001b[0m in \u001b[0;36m_flush\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     57\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"_timestamp\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"_timestamp\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\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     58\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_callback\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 59\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_callback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_step\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     60\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\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     61\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\u001b[0m in \u001b[0;36m_history_callback\u001b[0;34m(self, row, step)\u001b[0m\n\u001b[1;32m    804\u001b[0m             \u001b[0mnot_using_tensorboard\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwandb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpatched\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"tensorboard\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    805\u001b[0m             self._backend.interface.publish_history(\n\u001b[0;32m--> 806\u001b[0;31m                 \u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpublish_step\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnot_using_tensorboard\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    807\u001b[0m             )\n\u001b[1;32m    808\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/interface/interface.py\u001b[0m in \u001b[0;36mpublish_history\u001b[0;34m(self, data, step, run, publish_step)\u001b[0m\n\u001b[1;32m    224\u001b[0m             \u001b[0mitem\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\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    225\u001b[0m             \u001b[0mitem\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 226\u001b[0;31m             \u001b[0mitem\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue_json\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mjson_dumps_safer_history\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    227\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_publish_history\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    228\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/util.py\u001b[0m in \u001b[0;36mjson_dumps_safer_history\u001b[0;34m(obj, **kwargs)\u001b[0m\n\u001b[1;32m    653\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mjson_dumps_safer_history\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    654\u001b[0m     \u001b[0;34m\"\"\"Convert obj to json, with some extra encodable types, including histograms\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 655\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mWandBHistoryJSONEncoder\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    656\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    657\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/json/__init__.py\u001b[0m in \u001b[0;36mdumps\u001b[0;34m(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)\u001b[0m\n\u001b[1;32m    236\u001b[0m         \u001b[0mcheck_circular\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcheck_circular\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mallow_nan\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mallow_nan\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindent\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    237\u001b[0m         \u001b[0mseparators\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseparators\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdefault\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdefault\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msort_keys\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msort_keys\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 238\u001b[0;31m         **kw).encode(obj)\n\u001b[0m\u001b[1;32m    239\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    240\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/json/encoder.py\u001b[0m in \u001b[0;36mencode\u001b[0;34m(self, o)\u001b[0m\n\u001b[1;32m    197\u001b[0m         \u001b[0;31m# exceptions aren't as detailed.  The list call should be roughly\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    198\u001b[0m         \u001b[0;31m# equivalent to the PySequence_Fast that ''.join() would do.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 199\u001b[0;31m         \u001b[0mchunks\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miterencode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mo\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_one_shot\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\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    200\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchunks\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\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    201\u001b[0m             \u001b[0mchunks\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchunks\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/json/encoder.py\u001b[0m in \u001b[0;36miterencode\u001b[0;34m(self, o, _one_shot)\u001b[0m\n\u001b[1;32m    255\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkey_separator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitem_separator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_keys\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    256\u001b[0m                 self.skipkeys, _one_shot)\n\u001b[0;32m--> 257\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_iterencode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mo\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\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    258\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    259\u001b[0m def _make_iterencode(markers, _default, _encoder, _indent, _floatstr,\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/util.py\u001b[0m in \u001b[0;36mdefault\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    620\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mconverted\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    621\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 622\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mJSONEncoder\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdefault\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\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    623\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    624\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/json/encoder.py\u001b[0m in \u001b[0;36mdefault\u001b[0;34m(self, o)\u001b[0m\n\u001b[1;32m    177\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    178\u001b[0m         \"\"\"\n\u001b[0;32m--> 179\u001b[0;31m         raise TypeError(f'Object of type {o.__class__.__name__} '\n\u001b[0m\u001b[1;32m    180\u001b[0m                         f'is not JSON serializable')\n\u001b[1;32m    181\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mTypeError\u001b[0m: Object of type Figure is not JSON serializable"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6oEhPpXc56G_",
        "outputId": "169b2609-d6c6-4156-e2fe-a18163cdb046"
      },
      "source": [
        "wandb_logger.experiment.finish()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Problem finishing run\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1502, in _atexit_cleanup\n",
            "    self._on_finish()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1638, in _on_finish\n",
            "    self.history._flush()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_history.py\", line 59, in _flush\n",
            "    self._callback(row=self._data, step=self._step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 806, in _history_callback\n",
            "    row, step, publish_step=not_using_tensorboard\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/interface/interface.py\", line 217, in publish_history\n",
            "    data = data_types.history_dict_to_json(run, data, step=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2060, in history_dict_to_json\n",
            "    payload[key] = val_to_json(run, key, val, namespace=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2088, in val_to_json\n",
            "    val = Plotly.make_plot_media(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2010, in make_plot_media\n",
            "    val = util.matplotlib_to_plotly(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/util.py\", line 414, in matplotlib_to_plotly\n",
            "    return tools.mpl_to_plotly(obj)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/tools.py\", line 112, in mpl_to_plotly\n",
            "    matplotlylib.Exporter(renderer).run(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 51, in run\n",
            "    self.crawl_fig(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 116, in crawl_fig\n",
            "    props=utils.get_figure_properties(fig)):\n",
            "  File \"/usr/lib/python3.7/contextlib.py\", line 112, in __enter__\n",
            "    return next(self.gen)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/renderers/base.py\", line 45, in draw_figure\n",
            "    self.open_figure(fig=fig, props=props)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/renderer.py\", line 90, in open_figure\n",
            "    self.mpl_x_bounds, self.mpl_y_bounds = mpltools.get_axes_bounds(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mpltools.py\", line 265, in get_axes_bounds\n",
            "    x_min, y_min, x_max, y_max = min(x_min), min(y_min), max(x_max), max(y_max)\n",
            "ValueError: min() arg is an empty sequence\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[32m\u001b[41mERROR\u001b[0m Problem finishing run\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1502, in _atexit_cleanup\n",
            "    self._on_finish()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1638, in _on_finish\n",
            "    self.history._flush()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_history.py\", line 59, in _flush\n",
            "    self._callback(row=self._data, step=self._step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 806, in _history_callback\n",
            "    row, step, publish_step=not_using_tensorboard\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/interface/interface.py\", line 217, in publish_history\n",
            "    data = data_types.history_dict_to_json(run, data, step=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2060, in history_dict_to_json\n",
            "    payload[key] = val_to_json(run, key, val, namespace=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2088, in val_to_json\n",
            "    val = Plotly.make_plot_media(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2010, in make_plot_media\n",
            "    val = util.matplotlib_to_plotly(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/util.py\", line 414, in matplotlib_to_plotly\n",
            "    return tools.mpl_to_plotly(obj)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/tools.py\", line 112, in mpl_to_plotly\n",
            "    matplotlylib.Exporter(renderer).run(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 51, in run\n",
            "    self.crawl_fig(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 116, in crawl_fig\n",
            "    props=utils.get_figure_properties(fig)):\n",
            "  File \"/usr/lib/python3.7/contextlib.py\", line 112, in __enter__\n",
            "    return next(self.gen)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/renderers/base.py\", line 45, in draw_figure\n",
            "    self.open_figure(fig=fig, props=props)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/renderer.py\", line 90, in open_figure\n",
            "    self.mpl_x_bounds, self.mpl_y_bounds = mpltools.get_axes_bounds(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mpltools.py\", line 265, in get_axes_bounds\n",
            "    x_min, y_min, x_max, y_max = min(x_min), min(y_min), max(x_max), max(y_max)\n",
            "ValueError: min() arg is an empty sequence\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 483
        },
        "id": "-ZsnjxVs22jh",
        "outputId": "7a661af4-75ec-4872-ef8a-84200b3eb392"
      },
      "source": [
        "wandb_logger = WandbLogger(project='GH-2063',\n",
        "                           entity=\"repro\",\n",
        "                           name=\"no_list\",\n",
        "                           notes=\"Remove the list and pass the figure\")\n",
        "\n",
        "fig = plt.figure()\n",
        "\n",
        "wandb_logger.experiment.log({'examples': fig})"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33marig23498\u001b[0m (use `wandb login --relogin` to force relogin)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "                Tracking run with wandb version 0.10.26<br/>\n",
              "                Syncing run <strong style=\"color:#cdcd00\">no_list</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
              "                Project page: <a href=\"https://wandb.ai/repro/GH-2063\" target=\"_blank\">https://wandb.ai/repro/GH-2063</a><br/>\n",
              "                Run page: <a href=\"https://wandb.ai/repro/GH-2063/runs/2ticlzuk\" target=\"_blank\">https://wandb.ai/repro/GH-2063/runs/2ticlzuk</a><br/>\n",
              "                Run data is saved locally in <code>/content/wandb/run-20210414_054332-2ticlzuk</code><br/><br/>\n",
              "            "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-6-ec3607ce6b70>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mfig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\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      7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mwandb_logger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexperiment\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'examples'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mfig\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      9\u001b[0m \u001b[0mwandb_logger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexperiment\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfinish\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/python3.7/dist-packages/wandb/sdk/wandb_run.py\u001b[0m in \u001b[0;36mlog\u001b[0;34m(self, data, step, commit, sync)\u001b[0m\n\u001b[1;32m   1053\u001b[0m             \u001b[0mcommit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1054\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcommit\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1055\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_row_add\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\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   1056\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1057\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_row_update\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\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/python3.7/dist-packages/wandb/sdk/wandb_history.py\u001b[0m in \u001b[0;36m_row_add\u001b[0;34m(self, row)\u001b[0m\n\u001b[1;32m     42\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_row_add\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrow\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     43\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 44\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_flush\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     45\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_step\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     46\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\u001b[0m in \u001b[0;36mval_to_json\u001b[0;34m(run, key, val, namespace)\u001b[0m\n\u001b[1;32m   2086\u001b[0m         )\n\u001b[1;32m   2087\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_matplotlib_typename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtypename\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_plotly_typename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtypename\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-> 2088\u001b[0;31m         \u001b[0mval\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPlotly\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmake_plot_media\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\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   2089\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSixSequence\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mWBValue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mval\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   2090\u001b[0m         \u001b[0;32massert\u001b[0m \u001b[0mrun\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\u001b[0m in \u001b[0;36mmake_plot_media\u001b[0;34m(cls, val)\u001b[0m\n\u001b[1;32m   2008\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatplotlib_contains_images\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\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   2009\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mImage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2010\u001b[0;31m             \u001b[0mval\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatplotlib_to_plotly\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\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   2011\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2012\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/util.py\u001b[0m in \u001b[0;36mmatplotlib_to_plotly\u001b[0;34m(obj)\u001b[0m\n\u001b[1;32m    412\u001b[0m         \u001b[0mrequired\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"plotly is required to log interactive plots, install with: pip install plotly or convert the plot to an image with `wandb.Image(plt)`\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    413\u001b[0m     )\n\u001b[0;32m--> 414\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mtools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmpl_to_plotly\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\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    415\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    416\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/plotly/tools.py\u001b[0m in \u001b[0;36mmpl_to_plotly\u001b[0;34m(fig, resize, strip_style, verbose)\u001b[0m\n\u001b[1;32m    110\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mmatplotlylib\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    111\u001b[0m         \u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmatplotlylib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPlotlyRenderer\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--> 112\u001b[0;31m         \u001b[0mmatplotlylib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mExporter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\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    113\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mresize\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    114\u001b[0m             \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresize\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/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, fig)\u001b[0m\n\u001b[1;32m     49\u001b[0m             \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     50\u001b[0m             \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcrawl_fig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\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     52\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mstaticmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\u001b[0m in \u001b[0;36mcrawl_fig\u001b[0;34m(self, fig)\u001b[0m\n\u001b[1;32m    114\u001b[0m         \u001b[0;34m\"\"\"Crawl the figure and process all axes\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    115\u001b[0m         with self.renderer.draw_figure(fig=fig,\n\u001b[0;32m--> 116\u001b[0;31m                                        props=utils.get_figure_properties(fig)):\n\u001b[0m\u001b[1;32m    117\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0max\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxes\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    118\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcrawl_ax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/contextlib.py\u001b[0m in \u001b[0;36m__enter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    110\u001b[0m         \u001b[0;32mdel\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    111\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 112\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgen\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    113\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    114\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"generator didn't yield\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/renderers/base.py\u001b[0m in \u001b[0;36mdraw_figure\u001b[0;34m(self, fig, props)\u001b[0m\n\u001b[1;32m     43\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_current_fig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     44\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_fig_props\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprops\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 45\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprops\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprops\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     46\u001b[0m         \u001b[0;32myield\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     47\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfig\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/python3.7/dist-packages/plotly/matplotlylib/renderer.py\u001b[0m in \u001b[0;36mopen_figure\u001b[0;34m(self, fig, props)\u001b[0m\n\u001b[1;32m     88\u001b[0m             \u001b[0mhovermode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"closest\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     89\u001b[0m         )\n\u001b[0;32m---> 90\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmpl_x_bounds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmpl_y_bounds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmpltools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_axes_bounds\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\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     91\u001b[0m         margin = go.layout.Margin(\n\u001b[1;32m     92\u001b[0m             \u001b[0ml\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmpl_x_bounds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplotly_fig\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"layout\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"width\"\u001b[0m\u001b[0;34m]\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/python3.7/dist-packages/plotly/matplotlylib/mpltools.py\u001b[0m in \u001b[0;36mget_axes_bounds\u001b[0;34m(fig)\u001b[0m\n\u001b[1;32m    263\u001b[0m         \u001b[0my_min\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbounds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\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    264\u001b[0m         \u001b[0my_max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbounds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mbounds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m3\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--> 265\u001b[0;31m     \u001b[0mx_min\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_min\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx_max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_min\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_min\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_max\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    266\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mx_min\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx_max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0my_min\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    267\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: min() arg is an empty sequence"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "l0FHz89u6Bpo",
        "outputId": "b6e70fc9-1a28-4d1e-80a0-4f9014706727"
      },
      "source": [
        "wandb_logger.experiment.finish()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Problem finishing run\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1502, in _atexit_cleanup\n",
            "    self._on_finish()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1638, in _on_finish\n",
            "    self.history._flush()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_history.py\", line 59, in _flush\n",
            "    self._callback(row=self._data, step=self._step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 806, in _history_callback\n",
            "    row, step, publish_step=not_using_tensorboard\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/interface/interface.py\", line 217, in publish_history\n",
            "    data = data_types.history_dict_to_json(run, data, step=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2060, in history_dict_to_json\n",
            "    payload[key] = val_to_json(run, key, val, namespace=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2088, in val_to_json\n",
            "    val = Plotly.make_plot_media(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2010, in make_plot_media\n",
            "    val = util.matplotlib_to_plotly(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/util.py\", line 414, in matplotlib_to_plotly\n",
            "    return tools.mpl_to_plotly(obj)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/tools.py\", line 112, in mpl_to_plotly\n",
            "    matplotlylib.Exporter(renderer).run(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 51, in run\n",
            "    self.crawl_fig(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 116, in crawl_fig\n",
            "    props=utils.get_figure_properties(fig)):\n",
            "  File \"/usr/lib/python3.7/contextlib.py\", line 112, in __enter__\n",
            "    return next(self.gen)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/renderers/base.py\", line 45, in draw_figure\n",
            "    self.open_figure(fig=fig, props=props)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/renderer.py\", line 90, in open_figure\n",
            "    self.mpl_x_bounds, self.mpl_y_bounds = mpltools.get_axes_bounds(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mpltools.py\", line 265, in get_axes_bounds\n",
            "    x_min, y_min, x_max, y_max = min(x_min), min(y_min), max(x_max), max(y_max)\n",
            "ValueError: min() arg is an empty sequence\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[32m\u001b[41mERROR\u001b[0m Problem finishing run\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1502, in _atexit_cleanup\n",
            "    self._on_finish()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1638, in _on_finish\n",
            "    self.history._flush()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_history.py\", line 59, in _flush\n",
            "    self._callback(row=self._data, step=self._step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 806, in _history_callback\n",
            "    row, step, publish_step=not_using_tensorboard\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/interface/interface.py\", line 217, in publish_history\n",
            "    data = data_types.history_dict_to_json(run, data, step=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2060, in history_dict_to_json\n",
            "    payload[key] = val_to_json(run, key, val, namespace=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2088, in val_to_json\n",
            "    val = Plotly.make_plot_media(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2010, in make_plot_media\n",
            "    val = util.matplotlib_to_plotly(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/util.py\", line 414, in matplotlib_to_plotly\n",
            "    return tools.mpl_to_plotly(obj)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/tools.py\", line 112, in mpl_to_plotly\n",
            "    matplotlylib.Exporter(renderer).run(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 51, in run\n",
            "    self.crawl_fig(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 116, in crawl_fig\n",
            "    props=utils.get_figure_properties(fig)):\n",
            "  File \"/usr/lib/python3.7/contextlib.py\", line 112, in __enter__\n",
            "    return next(self.gen)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/renderers/base.py\", line 45, in draw_figure\n",
            "    self.open_figure(fig=fig, props=props)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/renderer.py\", line 90, in open_figure\n",
            "    self.mpl_x_bounds, self.mpl_y_bounds = mpltools.get_axes_bounds(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mpltools.py\", line 265, in get_axes_bounds\n",
            "    x_min, y_min, x_max, y_max = min(x_min), min(y_min), max(x_max), max(y_max)\n",
            "ValueError: min() arg is an empty sequence\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        },
        "id": "ghhtn6Tu3pWc",
        "outputId": "25eeb416-ae6f-4c8f-fcc8-3441d99addb3"
      },
      "source": [
        "wandb_logger = WandbLogger(project='GH-2063',\n",
        "                           entity=\"repro\",\n",
        "                           name=\"plt_obj\",\n",
        "                           notes=\"Now send the plt object instead\")\n",
        "\n",
        "fig = plt.figure()\n",
        "\n",
        "wandb_logger.experiment.log({'examples': plt})"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "                Tracking run with wandb version 0.10.26<br/>\n",
              "                Syncing run <strong style=\"color:#cdcd00\">plt_obj</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
              "                Project page: <a href=\"https://wandb.ai/repro/GH-2063\" target=\"_blank\">https://wandb.ai/repro/GH-2063</a><br/>\n",
              "                Run page: <a href=\"https://wandb.ai/repro/GH-2063/runs/1r8s9nrh\" target=\"_blank\">https://wandb.ai/repro/GH-2063/runs/1r8s9nrh</a><br/>\n",
              "                Run data is saved locally in <code>/content/wandb/run-20210414_054350-1r8s9nrh</code><br/><br/>\n",
              "            "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-8-2c27e295fafc>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mfig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\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      7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mwandb_logger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexperiment\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'examples'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mplt\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      9\u001b[0m \u001b[0mwandb_logger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexperiment\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfinish\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/python3.7/dist-packages/wandb/sdk/wandb_run.py\u001b[0m in \u001b[0;36mlog\u001b[0;34m(self, data, step, commit, sync)\u001b[0m\n\u001b[1;32m   1053\u001b[0m             \u001b[0mcommit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1054\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcommit\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1055\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_row_add\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\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   1056\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1057\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_row_update\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\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/python3.7/dist-packages/wandb/sdk/wandb_history.py\u001b[0m in \u001b[0;36m_row_add\u001b[0;34m(self, row)\u001b[0m\n\u001b[1;32m     42\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_row_add\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrow\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     43\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 44\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_flush\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     45\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_step\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     46\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_history.py\u001b[0m in \u001b[0;36m_flush\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     57\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"_timestamp\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"_timestamp\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\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     58\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_callback\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 59\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_callback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_step\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     60\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\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     61\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\u001b[0m in \u001b[0;36m_history_callback\u001b[0;34m(self, row, step)\u001b[0m\n\u001b[1;32m    804\u001b[0m             \u001b[0mnot_using_tensorboard\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwandb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpatched\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"tensorboard\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    805\u001b[0m             self._backend.interface.publish_history(\n\u001b[0;32m--> 806\u001b[0;31m                 \u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpublish_step\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnot_using_tensorboard\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    807\u001b[0m             )\n\u001b[1;32m    808\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/interface/interface.py\u001b[0m in \u001b[0;36mpublish_history\u001b[0;34m(self, data, step, run, publish_step)\u001b[0m\n\u001b[1;32m    215\u001b[0m     ) -> None:\n\u001b[1;32m    216\u001b[0m         \u001b[0mrun\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_run\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 217\u001b[0;31m         \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata_types\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhistory_dict_to_json\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\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[0m\n\u001b[0m\u001b[1;32m    218\u001b[0m         \u001b[0mhistory\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mHistoryRecord\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    219\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mpublish_step\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/python3.7/dist-packages/wandb/sdk/data_types.py\u001b[0m in \u001b[0;36mhistory_dict_to_json\u001b[0;34m(run, payload, step)\u001b[0m\n\u001b[1;32m   2058\u001b[0m             \u001b[0mpayload\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhistory_dict_to_json\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mval\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\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[0m\n\u001b[1;32m   2059\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2060\u001b[0;31m             \u001b[0mpayload\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mval_to_json\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mval\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnamespace\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[0m\n\u001b[0m\u001b[1;32m   2061\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2062\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mpayload\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\u001b[0m in \u001b[0;36mval_to_json\u001b[0;34m(run, key, val, namespace)\u001b[0m\n\u001b[1;32m   2086\u001b[0m         )\n\u001b[1;32m   2087\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_matplotlib_typename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtypename\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_plotly_typename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtypename\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-> 2088\u001b[0;31m         \u001b[0mval\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPlotly\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmake_plot_media\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\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   2089\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSixSequence\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mWBValue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mval\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   2090\u001b[0m         \u001b[0;32massert\u001b[0m \u001b[0mrun\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\u001b[0m in \u001b[0;36mmake_plot_media\u001b[0;34m(cls, val)\u001b[0m\n\u001b[1;32m   2008\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatplotlib_contains_images\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\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   2009\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mImage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2010\u001b[0;31m             \u001b[0mval\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mutil\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatplotlib_to_plotly\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\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   2011\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2012\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/wandb/util.py\u001b[0m in \u001b[0;36mmatplotlib_to_plotly\u001b[0;34m(obj)\u001b[0m\n\u001b[1;32m    412\u001b[0m         \u001b[0mrequired\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"plotly is required to log interactive plots, install with: pip install plotly or convert the plot to an image with `wandb.Image(plt)`\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    413\u001b[0m     )\n\u001b[0;32m--> 414\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mtools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmpl_to_plotly\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\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    415\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    416\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/plotly/tools.py\u001b[0m in \u001b[0;36mmpl_to_plotly\u001b[0;34m(fig, resize, strip_style, verbose)\u001b[0m\n\u001b[1;32m    110\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mmatplotlylib\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    111\u001b[0m         \u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmatplotlylib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPlotlyRenderer\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--> 112\u001b[0;31m         \u001b[0mmatplotlylib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mExporter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\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    113\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mresize\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    114\u001b[0m             \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresize\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/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, fig)\u001b[0m\n\u001b[1;32m     49\u001b[0m             \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     50\u001b[0m             \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcrawl_fig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\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     52\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mstaticmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\u001b[0m in \u001b[0;36mcrawl_fig\u001b[0;34m(self, fig)\u001b[0m\n\u001b[1;32m    114\u001b[0m         \u001b[0;34m\"\"\"Crawl the figure and process all axes\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    115\u001b[0m         with self.renderer.draw_figure(fig=fig,\n\u001b[0;32m--> 116\u001b[0;31m                                        props=utils.get_figure_properties(fig)):\n\u001b[0m\u001b[1;32m    117\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0max\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxes\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    118\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcrawl_ax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.7/contextlib.py\u001b[0m in \u001b[0;36m__enter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    110\u001b[0m         \u001b[0;32mdel\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    111\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 112\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgen\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    113\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    114\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"generator didn't yield\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/renderers/base.py\u001b[0m in \u001b[0;36mdraw_figure\u001b[0;34m(self, fig, props)\u001b[0m\n\u001b[1;32m     43\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_current_fig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     44\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_fig_props\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprops\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 45\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprops\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprops\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     46\u001b[0m         \u001b[0;32myield\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     47\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfig\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/python3.7/dist-packages/plotly/matplotlylib/renderer.py\u001b[0m in \u001b[0;36mopen_figure\u001b[0;34m(self, fig, props)\u001b[0m\n\u001b[1;32m     88\u001b[0m             \u001b[0mhovermode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"closest\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     89\u001b[0m         )\n\u001b[0;32m---> 90\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmpl_x_bounds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmpl_y_bounds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmpltools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_axes_bounds\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\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     91\u001b[0m         margin = go.layout.Margin(\n\u001b[1;32m     92\u001b[0m             \u001b[0ml\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmpl_x_bounds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplotly_fig\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"layout\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"width\"\u001b[0m\u001b[0;34m]\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/python3.7/dist-packages/plotly/matplotlylib/mpltools.py\u001b[0m in \u001b[0;36mget_axes_bounds\u001b[0;34m(fig)\u001b[0m\n\u001b[1;32m    263\u001b[0m         \u001b[0my_min\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbounds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\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    264\u001b[0m         \u001b[0my_max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbounds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mbounds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m3\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--> 265\u001b[0;31m     \u001b[0mx_min\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_min\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx_max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_min\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_min\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_max\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    266\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mx_min\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx_max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0my_min\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    267\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: min() arg is an empty sequence"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "huEdNFFi6FXw",
        "outputId": "f38a71a4-1948-44a7-aa9e-f197c17758de"
      },
      "source": [
        "wandb_logger.experiment.finish()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Problem finishing run\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1502, in _atexit_cleanup\n",
            "    self._on_finish()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1638, in _on_finish\n",
            "    self.history._flush()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_history.py\", line 59, in _flush\n",
            "    self._callback(row=self._data, step=self._step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 806, in _history_callback\n",
            "    row, step, publish_step=not_using_tensorboard\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/interface/interface.py\", line 217, in publish_history\n",
            "    data = data_types.history_dict_to_json(run, data, step=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2060, in history_dict_to_json\n",
            "    payload[key] = val_to_json(run, key, val, namespace=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2088, in val_to_json\n",
            "    val = Plotly.make_plot_media(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2010, in make_plot_media\n",
            "    val = util.matplotlib_to_plotly(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/util.py\", line 414, in matplotlib_to_plotly\n",
            "    return tools.mpl_to_plotly(obj)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/tools.py\", line 112, in mpl_to_plotly\n",
            "    matplotlylib.Exporter(renderer).run(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 51, in run\n",
            "    self.crawl_fig(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 116, in crawl_fig\n",
            "    props=utils.get_figure_properties(fig)):\n",
            "  File \"/usr/lib/python3.7/contextlib.py\", line 112, in __enter__\n",
            "    return next(self.gen)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/renderers/base.py\", line 45, in draw_figure\n",
            "    self.open_figure(fig=fig, props=props)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/renderer.py\", line 90, in open_figure\n",
            "    self.mpl_x_bounds, self.mpl_y_bounds = mpltools.get_axes_bounds(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mpltools.py\", line 265, in get_axes_bounds\n",
            "    x_min, y_min, x_max, y_max = min(x_min), min(y_min), max(x_max), max(y_max)\n",
            "ValueError: min() arg is an empty sequence\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[32m\u001b[41mERROR\u001b[0m Problem finishing run\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1502, in _atexit_cleanup\n",
            "    self._on_finish()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 1638, in _on_finish\n",
            "    self.history._flush()\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_history.py\", line 59, in _flush\n",
            "    self._callback(row=self._data, step=self._step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/wandb_run.py\", line 806, in _history_callback\n",
            "    row, step, publish_step=not_using_tensorboard\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/interface/interface.py\", line 217, in publish_history\n",
            "    data = data_types.history_dict_to_json(run, data, step=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2060, in history_dict_to_json\n",
            "    payload[key] = val_to_json(run, key, val, namespace=step)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2088, in val_to_json\n",
            "    val = Plotly.make_plot_media(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/sdk/data_types.py\", line 2010, in make_plot_media\n",
            "    val = util.matplotlib_to_plotly(val)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/wandb/util.py\", line 414, in matplotlib_to_plotly\n",
            "    return tools.mpl_to_plotly(obj)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/tools.py\", line 112, in mpl_to_plotly\n",
            "    matplotlylib.Exporter(renderer).run(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 51, in run\n",
            "    self.crawl_fig(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/exporter.py\", line 116, in crawl_fig\n",
            "    props=utils.get_figure_properties(fig)):\n",
            "  File \"/usr/lib/python3.7/contextlib.py\", line 112, in __enter__\n",
            "    return next(self.gen)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mplexporter/renderers/base.py\", line 45, in draw_figure\n",
            "    self.open_figure(fig=fig, props=props)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/renderer.py\", line 90, in open_figure\n",
            "    self.mpl_x_bounds, self.mpl_y_bounds = mpltools.get_axes_bounds(fig)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/mpltools.py\", line 265, in get_axes_bounds\n",
            "    x_min, y_min, x_max, y_max = min(x_min), min(y_min), max(x_max), max(y_max)\n",
            "ValueError: min() arg is an empty sequence\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 728,
          "referenced_widgets": [
            "28b3127dec4a4ede9187c234e4b12f86",
            "c07ea3420fe94ed28a3464749f6b40fb",
            "c61aacb43dbd4722b6681a1ef7674643",
            "4ce7ec97ac474692b8c0955827d3cc9d",
            "9f9dbd062e8646169dc24a88d0cbfdff",
            "a07d3d6129ec4a36b1cb7925876a0a8a",
            "4e1f39bb0993435ba7eb15df243fb0ff",
            "763fc2e8a22c4088b4bd8e9a53f055f6"
          ]
        },
        "id": "hWVV4Wbm0kdd",
        "outputId": "66ca9355-8287-4124-d536-7920ff47bdcf"
      },
      "source": [
        "wandb_logger = WandbLogger(project='GH-2063',\n",
        "                           entity=\"repro\",\n",
        "                           name=\"plot\",\n",
        "                           notes=\"Fill the plot and send the plt object\")\n",
        "\n",
        "fig = plt.figure()\n",
        "x = np.arange(10)\n",
        "y = 2.5 * np.sin(x / 20 * np.pi)\n",
        "yerr = np.linspace(0.05, 0.2, 10)\n",
        "\n",
        "plt.errorbar(x, y + 3, yerr=yerr, label='both limits (default)')\n",
        "\n",
        "plt.errorbar(x, y + 2, yerr=yerr, uplims=True, label='uplims=True')\n",
        "\n",
        "plt.errorbar(x, y + 1, yerr=yerr, uplims=True, lolims=True,\n",
        "             label='uplims=True, lolims=True')\n",
        "\n",
        "upperlimits = [True, False] * 5\n",
        "lowerlimits = [False, True] * 5\n",
        "plt.errorbar(x, y, yerr=yerr, uplims=upperlimits, lolims=lowerlimits,\n",
        "             label='subsets of uplims and lolims')\n",
        "\n",
        "plt.legend(loc='lower right')\n",
        "\n",
        "wandb_logger.experiment.log({'examples': plt})\n",
        "wandb_logger.experiment.finish()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "                Tracking run with wandb version 0.10.26<br/>\n",
              "                Syncing run <strong style=\"color:#cdcd00\">plot</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
              "                Project page: <a href=\"https://wandb.ai/repro/GH-2063\" target=\"_blank\">https://wandb.ai/repro/GH-2063</a><br/>\n",
              "                Run page: <a href=\"https://wandb.ai/repro/GH-2063/runs/z1khuzx0\" target=\"_blank\">https://wandb.ai/repro/GH-2063/runs/z1khuzx0</a><br/>\n",
              "                Run data is saved locally in <code>/content/wandb/run-20210414_054406-z1khuzx0</code><br/><br/>\n",
              "            "
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          "text": [
            "/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/renderer.py:474: UserWarning:\n",
            "\n",
            "Dang! That path collection is out of this world. I totally don't know what to do with it yet! Plotly can only import path collections linked to 'data' coordinates\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
            "\n",
            "Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
            "\n",
            "I found a path object that I don't think is part of a bar chart. Ignoring.\n",
            "\n"
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              "Find user logs for this run at: <code>/content/wandb/run-20210414_054406-z1khuzx0/logs/debug.log</code>"
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              "<h3>Run summary:</h3><br/><style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
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              "<tr><td>_runtime</td><td>4</td></tr><tr><td>_timestamp</td><td>1618379050</td></tr><tr><td>_step</td><td>0</td></tr></table>"
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              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
              "    </style><table class=\"wandb\">\n",
              "<tr><td>_runtime</td><td>▁</td></tr><tr><td>_timestamp</td><td>▁</td></tr><tr><td>_step</td><td>▁</td></tr></table><br/>"
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              "                    <br/>Synced <strong style=\"color:#cdcd00\">plot</strong>: <a href=\"https://wandb.ai/repro/GH-2063/runs/z1khuzx0\" target=\"_blank\">https://wandb.ai/repro/GH-2063/runs/z1khuzx0</a><br/>\n",
              "                "
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