bbbp.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "bbbp.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AxYquAxMfceL",
        "outputId": "ba2c457a-5a72-4e87-d283-34f20c180c89"
      },
      "source": [
        "!which python"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/usr/local/bin/python\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PwSjD8qlfzQm",
        "outputId": "7dc9a5cd-486d-4897-818f-f889e3d5ebdf"
      },
      "source": [
        "!python --version"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python 3.7.11\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9uvvOyIcf2Tp",
        "outputId": "4d0fdfae-4542-49f1-d1d1-d39c37a1f11e"
      },
      "source": [
        "%env PYTHONPATH="
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "env: PYTHONPATH=\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yst4OE-Ef4Zt",
        "outputId": "5e7e2c22-5e34-4b71-b5b0-98558447871c"
      },
      "source": [
        "! wget https://repo.anaconda.com/miniconda/Miniconda3-py37_4.9.2-Linux-x86_64.sh\n",
        "! chmod +x Miniconda3-py37_4.9.2-Linux-x86_64.sh\n",
        "! bash ./Miniconda3-py37_4.9.2-Linux-x86_64.sh -b -f -p /usr/local\n",
        "import sys\n",
        "sys.path.append('/usr/local/lib/python3.7/site-packages/')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2021-09-08 04:30:15--  https://repo.anaconda.com/miniconda/Miniconda3-py37_4.9.2-Linux-x86_64.sh\n",
            "Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.131.3, 104.16.130.3, 2606:4700::6810:8303, ...\n",
            "Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.131.3|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 90040905 (86M) [application/x-sh]\n",
            "Saving to: ‘Miniconda3-py37_4.9.2-Linux-x86_64.sh’\n",
            "\n",
            "Miniconda3-py37_4.9 100%[===================>]  85.87M   186MB/s    in 0.5s    \n",
            "\n",
            "2021-09-08 04:30:15 (186 MB/s) - ‘Miniconda3-py37_4.9.2-Linux-x86_64.sh’ saved [90040905/90040905]\n",
            "\n",
            "PREFIX=/usr/local\n",
            "Unpacking payload ...\n",
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\bdone\n",
            "Solving environment: - \b\b\\ \b\bdone\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local\n",
            "\n",
            "  added / updated specs:\n",
            "    - _libgcc_mutex==0.1=main\n",
            "    - brotlipy==0.7.0=py37h27cfd23_1003\n",
            "    - ca-certificates==2020.10.14=0\n",
            "    - certifi==2020.6.20=pyhd3eb1b0_3\n",
            "    - cffi==1.14.3=py37h261ae71_2\n",
            "    - chardet==3.0.4=py37h06a4308_1003\n",
            "    - conda-package-handling==1.7.2=py37h03888b9_0\n",
            "    - conda==4.9.2=py37h06a4308_0\n",
            "    - cryptography==3.2.1=py37h3c74f83_1\n",
            "    - idna==2.10=py_0\n",
            "    - ld_impl_linux-64==2.33.1=h53a641e_7\n",
            "    - libedit==3.1.20191231=h14c3975_1\n",
            "    - libffi==3.3=he6710b0_2\n",
            "    - libgcc-ng==9.1.0=hdf63c60_0\n",
            "    - libstdcxx-ng==9.1.0=hdf63c60_0\n",
            "    - ncurses==6.2=he6710b0_1\n",
            "    - openssl==1.1.1h=h7b6447c_0\n",
            "    - pip==20.2.4=py37h06a4308_0\n",
            "    - pycosat==0.6.3=py37h27cfd23_0\n",
            "    - pycparser==2.20=py_2\n",
            "    - pyopenssl==19.1.0=pyhd3eb1b0_1\n",
            "    - pysocks==1.7.1=py37_1\n",
            "    - python==3.7.9=h7579374_0\n",
            "    - readline==8.0=h7b6447c_0\n",
            "    - requests==2.24.0=py_0\n",
            "    - ruamel_yaml==0.15.87=py37h7b6447c_1\n",
            "    - setuptools==50.3.1=py37h06a4308_1\n",
            "    - six==1.15.0=py37h06a4308_0\n",
            "    - sqlite==3.33.0=h62c20be_0\n",
            "    - tk==8.6.10=hbc83047_0\n",
            "    - tqdm==4.51.0=pyhd3eb1b0_0\n",
            "    - urllib3==1.25.11=py_0\n",
            "    - wheel==0.35.1=pyhd3eb1b0_0\n",
            "    - xz==5.2.5=h7b6447c_0\n",
            "    - yaml==0.2.5=h7b6447c_0\n",
            "    - zlib==1.2.11=h7b6447c_3\n",
            "\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  _libgcc_mutex      pkgs/main/linux-64::_libgcc_mutex-0.1-main\n",
            "  brotlipy           pkgs/main/linux-64::brotlipy-0.7.0-py37h27cfd23_1003\n",
            "  ca-certificates    pkgs/main/linux-64::ca-certificates-2020.10.14-0\n",
            "  certifi            pkgs/main/noarch::certifi-2020.6.20-pyhd3eb1b0_3\n",
            "  cffi               pkgs/main/linux-64::cffi-1.14.3-py37h261ae71_2\n",
            "  chardet            pkgs/main/linux-64::chardet-3.0.4-py37h06a4308_1003\n",
            "  conda              pkgs/main/linux-64::conda-4.9.2-py37h06a4308_0\n",
            "  conda-package-han~ pkgs/main/linux-64::conda-package-handling-1.7.2-py37h03888b9_0\n",
            "  cryptography       pkgs/main/linux-64::cryptography-3.2.1-py37h3c74f83_1\n",
            "  idna               pkgs/main/noarch::idna-2.10-py_0\n",
            "  ld_impl_linux-64   pkgs/main/linux-64::ld_impl_linux-64-2.33.1-h53a641e_7\n",
            "  libedit            pkgs/main/linux-64::libedit-3.1.20191231-h14c3975_1\n",
            "  libffi             pkgs/main/linux-64::libffi-3.3-he6710b0_2\n",
            "  libgcc-ng          pkgs/main/linux-64::libgcc-ng-9.1.0-hdf63c60_0\n",
            "  libstdcxx-ng       pkgs/main/linux-64::libstdcxx-ng-9.1.0-hdf63c60_0\n",
            "  ncurses            pkgs/main/linux-64::ncurses-6.2-he6710b0_1\n",
            "  openssl            pkgs/main/linux-64::openssl-1.1.1h-h7b6447c_0\n",
            "  pip                pkgs/main/linux-64::pip-20.2.4-py37h06a4308_0\n",
            "  pycosat            pkgs/main/linux-64::pycosat-0.6.3-py37h27cfd23_0\n",
            "  pycparser          pkgs/main/noarch::pycparser-2.20-py_2\n",
            "  pyopenssl          pkgs/main/noarch::pyopenssl-19.1.0-pyhd3eb1b0_1\n",
            "  pysocks            pkgs/main/linux-64::pysocks-1.7.1-py37_1\n",
            "  python             pkgs/main/linux-64::python-3.7.9-h7579374_0\n",
            "  readline           pkgs/main/linux-64::readline-8.0-h7b6447c_0\n",
            "  requests           pkgs/main/noarch::requests-2.24.0-py_0\n",
            "  ruamel_yaml        pkgs/main/linux-64::ruamel_yaml-0.15.87-py37h7b6447c_1\n",
            "  setuptools         pkgs/main/linux-64::setuptools-50.3.1-py37h06a4308_1\n",
            "  six                pkgs/main/linux-64::six-1.15.0-py37h06a4308_0\n",
            "  sqlite             pkgs/main/linux-64::sqlite-3.33.0-h62c20be_0\n",
            "  tk                 pkgs/main/linux-64::tk-8.6.10-hbc83047_0\n",
            "  tqdm               pkgs/main/noarch::tqdm-4.51.0-pyhd3eb1b0_0\n",
            "  urllib3            pkgs/main/noarch::urllib3-1.25.11-py_0\n",
            "  wheel              pkgs/main/noarch::wheel-0.35.1-pyhd3eb1b0_0\n",
            "  xz                 pkgs/main/linux-64::xz-5.2.5-h7b6447c_0\n",
            "  yaml               pkgs/main/linux-64::yaml-0.2.5-h7b6447c_0\n",
            "  zlib               pkgs/main/linux-64::zlib-1.2.11-h7b6447c_3\n",
            "\n",
            "\n",
            "Preparing transaction: / \b\b- \b\b\\ \b\b| \b\bdone\n",
            "Executing transaction: - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
            "installation finished.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BjjUa8xYf7fJ",
        "outputId": "e146fc2d-dd0f-43a7-87e6-58f60dd7299f"
      },
      "source": [
        "!which conda  # should return /usr/local/bin/conda"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/usr/local/bin/conda\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DH4Lr8h3f-cl",
        "outputId": "5572b608-1e95-4d88-afd9-e501275ad2ba"
      },
      "source": [
        "!ls /usr/local/lib/python3.7/dist-packages"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "absl\n",
            "absl_py-0.12.0.dist-info\n",
            "alabaster\n",
            "alabaster-0.7.12.dist-info\n",
            "albumentations\n",
            "albumentations-0.1.12.dist-info\n",
            "altair\n",
            "altair-4.1.0.dist-info\n",
            "apiclient\n",
            "appdirs-1.4.4.dist-info\n",
            "appdirs.py\n",
            "apt\n",
            "apt_inst.cpython-37m-x86_64-linux-gnu.so\n",
            "apt_inst.pyi\n",
            "apt_pkg.cpython-37m-x86_64-linux-gnu.so\n",
            "apt_pkg.pyi\n",
            "aptsources\n",
            "argcomplete\n",
            "argcomplete-1.12.3.dist-info\n",
            "argon2\n",
            "argon2_cffi-21.1.0.dist-info\n",
            "arviz\n",
            "arviz-0.11.2.dist-info\n",
            "astor\n",
            "astor-0.8.1.dist-info\n",
            "astropy\n",
            "astropy-4.3.1.dist-info\n",
            "astunparse\n",
            "astunparse-1.6.3.dist-info\n",
            "atari_py\n",
            "atari_py-0.2.9.dist-info\n",
            "atari_py.libs\n",
            "atomicwrites\n",
            "atomicwrites-1.4.0.dist-info\n",
            "attr\n",
            "attrs-21.2.0.dist-info\n",
            "audioread\n",
            "audioread-2.1.9.dist-info\n",
            "autograd\n",
            "autograd-1.3.dist-info\n",
            "babel\n",
            "Babel-2.9.1.dist-info\n",
            "backcall\n",
            "backcall-0.2.0.dist-info\n",
            "beautifulsoup4-4.6.3.dist-info\n",
            "bin\n",
            "bleach\n",
            "bleach-4.0.0.dist-info\n",
            "blis\n",
            "blis-0.4.1.dist-info\n",
            "bokeh\n",
            "bokeh-2.3.3.dist-info\n",
            "bottleneck\n",
            "Bottleneck-1.3.2.dist-info\n",
            "branca\n",
            "branca-0.4.2.dist-info\n",
            "bs4\n",
            "bs4-0.0.1.dist-info\n",
            "bson\n",
            "cachecontrol\n",
            "CacheControl-0.12.6.dist-info\n",
            "cached_property-1.5.2.dist-info\n",
            "cached_property.py\n",
            "cachetools\n",
            "cachetools-4.2.2.dist-info\n",
            "caffe2\n",
            "catalogue-1.0.0.dist-info\n",
            "catalogue.py\n",
            "certifi\n",
            "certifi-2021.5.30.dist-info\n",
            "cffi\n",
            "cffi-1.14.6.dist-info\n",
            "_cffi_backend.cpython-37m-x86_64-linux-gnu.so\n",
            "cffi.libs\n",
            "cftime\n",
            "cftime-1.5.0.dist-info\n",
            "chardet\n",
            "chardet-3.0.4.dist-info\n",
            "charset_normalizer\n",
            "charset_normalizer-2.0.4.dist-info\n",
            "chess\n",
            "clang\n",
            "clang-5.0.dist-info\n",
            "click\n",
            "click-7.1.2.dist-info\n",
            "client\n",
            "cloudpickle\n",
            "cloudpickle-1.3.0.dist-info\n",
            "cmake\n",
            "cmake-3.12.0.dist-info\n",
            "cmdstanpy\n",
            "cmdstanpy-0.9.5.dist-info\n",
            "colab\n",
            "colorcet\n",
            "colorcet-2.0.6.dist-info\n",
            "colorlover\n",
            "colorlover-0.3.0.dist-info\n",
            "community\n",
            "community-1.0.0b1.dist-info\n",
            "contextlib2-0.5.5.dist-info\n",
            "contextlib2.py\n",
            "convertdate\n",
            "convertdate-2.3.2.dist-info\n",
            "coverage\n",
            "coverage-3.7.1.dist-info\n",
            "coveralls\n",
            "coveralls-0.5.dist-info\n",
            "crcmod\n",
            "crcmod-1.7.dist-info\n",
            "cufflinks\n",
            "cufflinks-0.17.3.dist-info\n",
            "cupy\n",
            "cupy_backends\n",
            "cupy_cuda101-9.1.0.dist-info\n",
            "cupyx\n",
            "cv2\n",
            "_cvxcore.cpython-37m-x86_64-linux-gnu.so\n",
            "cvxopt\n",
            "cvxopt-1.2.6.dist-info\n",
            "cvxopt.libs\n",
            "cvxpy\n",
            "cvxpy-1.0.31.dist-info\n",
            "cycler-0.10.0.dist-info\n",
            "cycler.py\n",
            "cymem\n",
            "cymem-2.0.5.dist-info\n",
            "Cython\n",
            "Cython-0.29.24.dist-info\n",
            "cython.py\n",
            "daft-0.0.4.dist-info\n",
            "daft.py\n",
            "dask\n",
            "dask-2.12.0.dist-info\n",
            "datascience\n",
            "datascience-0.10.6.dist-info\n",
            "dateutil\n",
            "debugpy\n",
            "debugpy-1.0.0.dist-info\n",
            "decorator-4.4.2.dist-info\n",
            "decorator.py\n",
            "defusedxml\n",
            "defusedxml-0.7.1.dist-info\n",
            "descartes\n",
            "descartes-1.1.0.dist-info\n",
            "dill\n",
            "dill-0.3.4.dist-info\n",
            "distributed\n",
            "distributed-1.25.3.dist-info\n",
            "_distutils_hack\n",
            "distutils-precedence.pth\n",
            "dlib-19.18.0.dist-info\n",
            "dlib.cpython-37m-x86_64-linux-gnu.so\n",
            "dm_tree-0.1.6.dist-info\n",
            "docopt-0.6.2.dist-info\n",
            "docopt.py\n",
            "docs\n",
            "docutils\n",
            "docutils-0.17.1.dist-info\n",
            "dopamine\n",
            "dopamine_rl-1.0.5.dist-info\n",
            "dot_parser.py\n",
            "earthengine_api-0.1.278.dist-info\n",
            "easydict\n",
            "easydict-1.9.dist-info\n",
            "ecos\n",
            "ecos-2.0.7.post1.dist-info\n",
            "_ecos.cpython-37m-x86_64-linux-gnu.so\n",
            "editdistance\n",
            "editdistance-0.5.3.dist-info\n",
            "ee\n",
            "en_core_web_sm\n",
            "en_core_web_sm-2.2.5.dist-info\n",
            "entrypoints-0.3.dist-info\n",
            "entrypoints.py\n",
            "ephem\n",
            "ephem-4.0.0.2.dist-info\n",
            "erfa\n",
            "et_xmlfile\n",
            "et_xmlfile-1.1.0.dist-info\n",
            "examples\n",
            "fa2\n",
            "fa2-0.3.5.dist-info\n",
            "fastai\n",
            "fastai-1.0.61.dist-info\n",
            "fastdtw\n",
            "fastdtw-0.3.4.dist-info\n",
            "fastprogress\n",
            "fastprogress-1.0.0.dist-info\n",
            "fastrlock\n",
            "fastrlock-0.6.dist-info\n",
            "fbprophet\n",
            "fbprophet-0.7.1-py3.7.egg-info\n",
            "feather\n",
            "feather_format-0.4.1.dist-info\n",
            "filelock-3.0.12.dist-info\n",
            "filelock.py\n",
            "firebase_admin\n",
            "firebase_admin-4.4.0.dist-info\n",
            "fix_yahoo_finance\n",
            "fix_yahoo_finance-0.0.22.dist-info\n",
            "flask\n",
            "Flask-1.1.4.dist-info\n",
            "flatbuffers\n",
            "flatbuffers-1.12.dist-info\n",
            "folium\n",
            "folium-0.8.3.dist-info\n",
            "future\n",
            "future-0.16.0.dist-info\n",
            "gast\n",
            "gast-0.4.0.dist-info\n",
            "GDAL-2.2.2.dist-info\n",
            "gdalconst.py\n",
            "gdalnumeric.py\n",
            "gdal.py\n",
            "gdown\n",
            "gdown-3.6.4.dist-info\n",
            "gensim\n",
            "gensim-3.6.0.dist-info\n",
            "geographiclib\n",
            "geographiclib-1.52.dist-info\n",
            "geopy\n",
            "geopy-1.17.0.dist-info\n",
            "gin\n",
            "gin_config-0.4.0.dist-info\n",
            "github2pypi\n",
            "glob2\n",
            "glob2-0.7.dist-info\n",
            "gnm.py\n",
            "google\n",
            "google-2.0.3.dist-info\n",
            "googleapiclient\n",
            "google_api_core-1.26.3.dist-info\n",
            "google_api_core-1.26.3-py3.9-nspkg.pth\n",
            "google_api_python_client-1.12.8.dist-info\n",
            "googleapis_common_protos-1.53.0.dist-info\n",
            "googleapis_common_protos-1.53.0-py3.9-nspkg.pth\n",
            "google_auth-1.34.0.dist-info\n",
            "google_auth-1.34.0-py3.9-nspkg.pth\n",
            "google_auth_httplib2-0.0.4.dist-info\n",
            "google_auth_httplib2.py\n",
            "google_auth_oauthlib\n",
            "google_auth_oauthlib-0.4.5.dist-info\n",
            "google_cloud_bigquery-1.21.0.dist-info\n",
            "google_cloud_bigquery-1.21.0-py3.6-nspkg.pth\n",
            "google_cloud_bigquery_storage-1.1.0.dist-info\n",
            "google_cloud_bigquery_storage-1.1.0-py3.8-nspkg.pth\n",
            "google_cloud_core-1.0.3.dist-info\n",
            "google_cloud_core-1.0.3-py3.6-nspkg.pth\n",
            "google_cloud_datastore-1.8.0.dist-info\n",
            "google_cloud_datastore-1.8.0-py3.6-nspkg.pth\n",
            "google_cloud_firestore-1.7.0.dist-info\n",
            "google_cloud_firestore-1.7.0-py3.8-nspkg.pth\n",
            "google_cloud_language-1.2.0.dist-info\n",
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            "google_cloud_storage-1.18.1-py3.7-nspkg.pth\n",
            "google_cloud_translate-1.5.0.dist-info\n",
            "google_cloud_translate-1.5.0-py3.6-nspkg.pth\n",
            "google_colab-1.0.0.dist-info\n",
            "google_colab-1.0.0-py3.7-nspkg.pth\n",
            "google_drive_downloader\n",
            "googledrivedownloader-0.4.dist-info\n",
            "google_pasta-0.2.0.dist-info\n",
            "google_resumable_media-0.4.1.dist-info\n",
            "google_resumable_media-0.4.1-py3.6-nspkg.pth\n",
            "googlesearch\n",
            "graphviz\n",
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            "greenlet\n",
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            "grpc\n",
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            "gspread\n",
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            "gspread_dataframe-3.0.8.dist-info\n",
            "gspread_dataframe.py\n",
            "gym\n",
            "gym-0.17.3.dist-info\n",
            "h5py\n",
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            "h5py.libs\n",
            "HeapDict-1.0.1.dist-info\n",
            "heapdict.py\n",
            "helper\n",
            "hijri_converter\n",
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            "holidays\n",
            "holidays-0.10.5.2.dist-info\n",
            "holoviews\n",
            "holoviews-1.14.5.dist-info\n",
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            "html5lib-1.0.1.dist-info\n",
            "httpimport-0.5.18.dist-info\n",
            "httpimport.py\n",
            "httplib2\n",
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            "httplib2shim\n",
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            "humanize\n",
            "humanize-0.5.1.dist-info\n",
            "hyperopt\n",
            "hyperopt-0.1.2.dist-info\n",
            "ideep4py\n",
            "ideep4py-2.0.0.post3.dist-info\n",
            "idna\n",
            "idna-2.10.dist-info\n",
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            "imagesize.py\n",
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            "imblearn\n",
            "imblearn-0.0.dist-info\n",
            "imgaug\n",
            "imgaug-0.2.9.dist-info\n",
            "importlib_metadata\n",
            "importlib_metadata-4.6.4.dist-info\n",
            "importlib_resources\n",
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            "imutils\n",
            "imutils-0.5.4.dist-info\n",
            "inflect-2.1.0.dist-info\n",
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            "iniconfig\n",
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            "intervaltree\n",
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            "ipywidgets\n",
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            "isympy.py\n",
            "itsdangerous\n",
            "itsdangerous-1.1.0.dist-info\n",
            "jax\n",
            "jax-0.2.19.dist-info\n",
            "jaxlib\n",
            "jaxlib-0.1.70+cuda110.dist-info\n",
            "jdcal-1.4.1.dist-info\n",
            "jdcal.py\n",
            "jedi\n",
            "jedi-0.18.0.dist-info\n",
            "jieba\n",
            "jieba-0.42.1.dist-info\n",
            "jinja2\n",
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            "joblib\n",
            "joblib-1.0.1.dist-info\n",
            "jpeg4py\n",
            "jpeg4py-0.1.4.dist-info\n",
            "jsonschema\n",
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            "jupyter_client\n",
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            "jupyter_console\n",
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            "jupyterlab_widgets\n",
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            "jupyter.py\n",
            "kaggle\n",
            "kaggle-1.5.12.dist-info\n",
            "kapre\n",
            "kapre-0.3.5.dist-info\n",
            "keras\n",
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            "keras_preprocessing\n",
            "Keras_Preprocessing-1.1.2.dist-info\n",
            "keras_vis-0.4.1.dist-info\n",
            "kiwisolver-1.3.1.dist-info\n",
            "kiwisolver.cpython-37m-x86_64-linux-gnu.so\n",
            "korean_lunar_calendar\n",
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            "libfuturize\n",
            "libpasteurize\n",
            "librosa\n",
            "librosa-0.8.1.dist-info\n",
            "lightgbm\n",
            "lightgbm-2.2.3.dist-info\n",
            "llvmlite\n",
            "llvmlite-0.34.0.dist-info\n",
            "lmdb\n",
            "lmdb-0.99.dist-info\n",
            "lunarcalendar\n",
            "LunarCalendar-0.0.9.dist-info\n",
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            "lxml-4.2.6.dist-info\n",
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            "matplotlib_inline\n",
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            "matplotlib.libs\n",
            "matplotlib_venn\n",
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            "Misc\n",
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            "mistune.py\n",
            "mizani\n",
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            "mlxtend\n",
            "mlxtend-0.14.0.dist-info\n",
            "more_itertools\n",
            "more_itertools-8.8.0.dist-info\n",
            "moviepy\n",
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            "mpl_toolkits\n",
            "mpmath\n",
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            "_multiprocess\n",
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            "netCDF4\n",
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            "nltk\n",
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            "pytz\n",
            "pytz-2018.9.dist-info\n",
            "pyviz_comms\n",
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            "regex\n",
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            "requests\n",
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            "requests_oauthlib\n",
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            "resampy\n",
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            "_rinterface_cffi_abi.py\n",
            "_rinterface_cffi_api.abi3.so\n",
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            "textblob-0.15.3.dist-info\n",
            "text_unidecode\n",
            "text_unidecode-1.3.dist-info\n",
            "theano\n",
            "Theano_PyMC-1.1.2.dist-info\n",
            "thinc\n",
            "thinc-7.4.0.dist-info\n",
            "tifffile\n",
            "tifffile-2021.8.30.dist-info\n",
            "tlz\n",
            "toml\n",
            "toml-0.10.2.dist-info\n",
            "tomli\n",
            "tomli-1.2.1.dist-info\n",
            "toolz\n",
            "toolz-0.11.1.dist-info\n",
            "torch\n",
            "torch-1.9.0+cu102.dist-info\n",
            "torchsummary\n",
            "torchsummary-1.5.1.dist-info\n",
            "torchtext\n",
            "torchtext-0.10.0.dist-info\n",
            "torchvision\n",
            "torchvision-0.10.0+cu102.dist-info\n",
            "torchvision.libs\n",
            "tornado\n",
            "tornado-5.1.1.dist-info\n",
            "tqdm\n",
            "tqdm-4.62.0.dist-info\n",
            "traitlets\n",
            "traitlets-5.0.5.dist-info\n",
            "tree\n",
            "tweepy\n",
            "tweepy-3.10.0.dist-info\n",
            "typeguard\n",
            "typeguard-2.7.1.dist-info\n",
            "typing_extensions-3.7.4.3.dist-info\n",
            "typing_extensions.py\n",
            "tzlocal\n",
            "tzlocal-1.5.1.dist-info\n",
            "uritemplate\n",
            "uritemplate-3.0.1.dist-info\n",
            "urllib3\n",
            "urllib3-1.24.3.dist-info\n",
            "vega_datasets\n",
            "vega_datasets-0.9.0.dist-info\n",
            "vis\n",
            "wasabi\n",
            "wasabi-0.8.2.dist-info\n",
            "wcwidth\n",
            "wcwidth-0.2.5.dist-info\n",
            "webencodings\n",
            "webencodings-0.5.1.dist-info\n",
            "werkzeug\n",
            "Werkzeug-1.0.1.dist-info\n",
            "wheel\n",
            "wheel-0.37.0.dist-info\n",
            "widgetsnbextension\n",
            "widgetsnbextension-3.5.1.dist-info\n",
            "wordcloud\n",
            "wordcloud-1.5.0.dist-info\n",
            "wrapt\n",
            "wrapt-1.12.1.dist-info\n",
            "xarray\n",
            "xarray-0.18.2.dist-info\n",
            "xgboost\n",
            "xgboost-0.90.dist-info\n",
            "xlrd\n",
            "xlrd-1.1.0.dist-info\n",
            "xlwt\n",
            "xlwt-1.3.0.dist-info\n",
            "yaml\n",
            "yellowbrick\n",
            "yellowbrick-0.9.1.dist-info\n",
            "zict\n",
            "zict-2.0.0.dist-info\n",
            "zipp-3.5.0.dist-info\n",
            "zipp.py\n",
            "zmq\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jA5drWskgIdR",
        "outputId": "dccf8af6-20f4-49b8-b101-4202f11884a9"
      },
      "source": [
        "!conda create -n testenv python==3.7"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "Solving environment: / \b\bfailed with repodata from current_repodata.json, will retry with next repodata source.\n",
            "Collecting package metadata (repodata.json): \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
            "Solving environment: - \b\b\\ \b\b| \b\b/ \b\bdone\n",
            "\n",
            "\n",
            "==> WARNING: A newer version of conda exists. <==\n",
            "  current version: 4.9.2\n",
            "  latest version: 4.10.3\n",
            "\n",
            "Please update conda by running\n",
            "\n",
            "    $ conda update -n base -c defaults conda\n",
            "\n",
            "\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local/envs/testenv\n",
            "\n",
            "  added / updated specs:\n",
            "    - python==3.7\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    _openmp_mutex-4.5          |            1_gnu          22 KB\n",
            "    ca-certificates-2021.7.5   |       h06a4308_1         113 KB\n",
            "    certifi-2021.5.30          |   py37h06a4308_0         139 KB\n",
            "    libedit-3.1.20210714       |       h7f8727e_0         165 KB\n",
            "    libffi-3.2.1               |    hf484d3e_1007          48 KB\n",
            "    libgcc-ng-9.3.0            |      h5101ec6_17         4.8 MB\n",
            "    libgomp-9.3.0              |      h5101ec6_17         311 KB\n",
            "    libstdcxx-ng-9.3.0         |      hd4cf53a_17         3.1 MB\n",
            "    openssl-1.0.2u             |       h7b6447c_0         2.2 MB\n",
            "    pip-21.2.2                 |   py37h06a4308_0         1.8 MB\n",
            "    python-3.7.0               |       h6e4f718_3        27.2 MB\n",
            "    readline-7.0               |       h7b6447c_5         324 KB\n",
            "    setuptools-52.0.0          |   py37h06a4308_0         710 KB\n",
            "    wheel-0.37.0               |     pyhd3eb1b0_1          33 KB\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:        40.9 MB\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  _libgcc_mutex      pkgs/main/linux-64::_libgcc_mutex-0.1-main\n",
            "  _openmp_mutex      pkgs/main/linux-64::_openmp_mutex-4.5-1_gnu\n",
            "  ca-certificates    pkgs/main/linux-64::ca-certificates-2021.7.5-h06a4308_1\n",
            "  certifi            pkgs/main/linux-64::certifi-2021.5.30-py37h06a4308_0\n",
            "  libedit            pkgs/main/linux-64::libedit-3.1.20210714-h7f8727e_0\n",
            "  libffi             pkgs/main/linux-64::libffi-3.2.1-hf484d3e_1007\n",
            "  libgcc-ng          pkgs/main/linux-64::libgcc-ng-9.3.0-h5101ec6_17\n",
            "  libgomp            pkgs/main/linux-64::libgomp-9.3.0-h5101ec6_17\n",
            "  libstdcxx-ng       pkgs/main/linux-64::libstdcxx-ng-9.3.0-hd4cf53a_17\n",
            "  ncurses            pkgs/main/linux-64::ncurses-6.2-he6710b0_1\n",
            "  openssl            pkgs/main/linux-64::openssl-1.0.2u-h7b6447c_0\n",
            "  pip                pkgs/main/linux-64::pip-21.2.2-py37h06a4308_0\n",
            "  python             pkgs/main/linux-64::python-3.7.0-h6e4f718_3\n",
            "  readline           pkgs/main/linux-64::readline-7.0-h7b6447c_5\n",
            "  setuptools         pkgs/main/linux-64::setuptools-52.0.0-py37h06a4308_0\n",
            "  sqlite             pkgs/main/linux-64::sqlite-3.33.0-h62c20be_0\n",
            "  tk                 pkgs/main/linux-64::tk-8.6.10-hbc83047_0\n",
            "  wheel              pkgs/main/noarch::wheel-0.37.0-pyhd3eb1b0_1\n",
            "  xz                 pkgs/main/linux-64::xz-5.2.5-h7b6447c_0\n",
            "  zlib               pkgs/main/linux-64::zlib-1.2.11-h7b6447c_3\n",
            "\n",
            "\n",
            "Proceed ([y]/n)? y\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages\n",
            "libgcc-ng-9.3.0      | 4.8 MB    | : 100% 1.0/1 [00:00<00:00,  3.82it/s]               \n",
            "libstdcxx-ng-9.3.0   | 3.1 MB    | : 100% 1.0/1 [00:00<00:00,  6.81it/s]\n",
            "libgomp-9.3.0        | 311 KB    | : 100% 1.0/1 [00:00<00:00, 18.08it/s]\n",
            "openssl-1.0.2u       | 2.2 MB    | : 100% 1.0/1 [00:00<00:00,  8.16it/s]\n",
            "certifi-2021.5.30    | 139 KB    | : 100% 1.0/1 [00:00<00:00, 19.30it/s]\n",
            "readline-7.0         | 324 KB    | : 100% 1.0/1 [00:00<00:00, 19.33it/s]\n",
            "ca-certificates-2021 | 113 KB    | : 100% 1.0/1 [00:00<00:00, 21.76it/s]\n",
            "pip-21.2.2           | 1.8 MB    | : 100% 1.0/1 [00:00<00:00,  5.20it/s]\n",
            "wheel-0.37.0         | 33 KB     | : 100% 1.0/1 [00:00<00:00, 20.34it/s]\n",
            "libedit-3.1.20210714 | 165 KB    | : 100% 1.0/1 [00:00<00:00, 18.43it/s]\n",
            "_openmp_mutex-4.5    | 22 KB     | : 100% 1.0/1 [00:00<00:00, 34.88it/s]\n",
            "python-3.7.0         | 27.2 MB   | : 100% 1.0/1 [00:01<00:00,  1.02s/it]               \n",
            "setuptools-52.0.0    | 710 KB    | : 100% 1.0/1 [00:00<00:00,  8.54it/s]\n",
            "libffi-3.2.1         | 48 KB     | : 100% 1.0/1 [00:00<00:00, 14.76it/s]\n",
            "Preparing transaction: \\ \b\b| \b\b/ \b\bdone\n",
            "Verifying transaction: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "Executing transaction: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "#\n",
            "# To activate this environment, use\n",
            "#\n",
            "#     $ conda activate testenv\n",
            "#\n",
            "# To deactivate an active environment, use\n",
            "#\n",
            "#     $ conda deactivate\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jPmRNkxwgPYz",
        "outputId": "1e7d061a-eb71-48c7-8940-179e74c26647"
      },
      "source": [
        "!git clone https://github.com/tencent-ailab/grover.git"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'grover'...\n",
            "remote: Enumerating objects: 72, done.\u001b[K\n",
            "remote: Counting objects: 100% (72/72), done.\u001b[K\n",
            "remote: Compressing objects: 100% (68/68), done.\u001b[K\n",
            "remote: Total 72 (delta 11), reused 57 (delta 2), pack-reused 0\u001b[K\n",
            "Unpacking objects: 100% (72/72), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ToJoB_MvgZMy",
        "outputId": "9ae7f463-2420-4eb5-a655-23dc4ca7fcd2"
      },
      "source": [
        "!source activate testenv && conda env list"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "# conda environments:\n",
            "#\n",
            "base                     /usr/local\n",
            "testenv               *  /usr/local/envs/testenv\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XG-th9srrVTY"
      },
      "source": [
        "!conda config --add channels pytorch\n",
        "!conda config --add channels rdkit\n",
        "!conda config --add channels conda-forge\n",
        "!conda config --add channels rmg"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1iBcbdUcjJRS",
        "outputId": "1ddda0ad-04f6-4518-be90-c27d42114156"
      },
      "source": [
        "!conda install --file grover/requirements.txt --yes"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
            "Solving environment: - \b\bfailed with initial frozen solve. Retrying with flexible solve.\n",
            "Collecting package metadata (repodata.json): | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
            "Solving environment: - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| y\n",
            "\b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n",
            "\n",
            "\n",
            "==> WARNING: A newer version of conda exists. <==\n",
            "  current version: 4.9.2\n",
            "  latest version: 4.10.3\n",
            "\n",
            "Please update conda by running\n",
            "\n",
            "    $ conda update -n base -c defaults conda\n",
            "\n",
            "\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local\n",
            "\n",
            "  added / updated specs:\n",
            "    - boost-cpp==1.68.0=h11c811c_1000\n",
            "    - boost==1.68.0=py36h8619c78_1001\n",
            "    - descriptastorus==2.2.0=py_0\n",
            "    - numpy-base==1.16.4=py36hde5b4d6_0\n",
            "    - numpy==1.16.4=py36h7e9f1db_0\n",
            "    - pandas==0.25.0=py36hb3f55d8_0\n",
            "    - python==3.6.8=h0371630_0\n",
            "    - pytorch==1.1.0=py3.6_cuda9.0.176_cudnn7.5.1_0\n",
            "    - rdkit==2019.03.4.0=py36hc20afe1_1\n",
            "    - readline==7.0=h7b6447c_5\n",
            "    - scikit-learn==0.21.2=py36hcdab131_1\n",
            "    - scipy==1.3.0=py36h921218d_1\n",
            "    - tensorboard==1.13.1=py36_0\n",
            "    - torchvision==0.3.0=py36_cu9.0.176_1\n",
            "    - tqdm==4.32.1=py_0\n",
            "    - typing==3.6.4=py36_0\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    blas-1.0                   |              mkl           1 KB  conda-forge\n",
            "    boost-1.68.0               |py36h8619c78_1001         325 KB  conda-forge\n",
            "    boost-cpp-1.68.0           |    h11c811c_1000        20.5 MB  conda-forge\n",
            "    brotlipy-0.7.0             |py36h8c4c3a4_1000         346 KB  rmg\n",
            "    bzip2-1.0.8                |       h516909a_3         398 KB  conda-forge\n",
            "    ca-certificates-2020.6.20  |       hecda079_0         145 KB  rmg\n",
            "    cairo-1.16.0               |    h18b612c_1001         1.5 MB  conda-forge\n",
            "    certifi-2020.6.20          |   py36h9f0ad1d_0         151 KB  rmg\n",
            "    cffi-1.14.4                |   py36h211aa47_0         224 KB  conda-forge\n",
            "    chardet-3.0.4              |py36h9f0ad1d_1006         188 KB  rmg\n",
            "    conda-4.10.3               |   py36h5fab9bb_0         3.1 MB  conda-forge\n",
            "    conda-package-handling-1.7.2|   py36he6145b8_0         925 KB  conda-forge\n",
            "    cryptography-2.9.2         |   py36h45558ae_0         613 KB  rmg\n",
            "    cudatoolkit-9.0            |       h13b8566_0       237.0 MB\n",
            "    dataclasses-0.8            |     pyh787bdff_2          22 KB  conda-forge\n",
            "    descriptastorus-2.2.0      |             py_0          63 KB  rmg\n",
            "    fontconfig-2.13.1          |    he4413a7_1000         327 KB  conda-forge\n",
            "    freetype-2.10.4            |       h7ca028e_0         912 KB  conda-forge\n",
            "    gettext-0.19.8.1           |    hf34092f_1004         3.6 MB  conda-forge\n",
            "    glib-2.66.3                |       h58526e2_0         500 KB  conda-forge\n",
            "    icu-58.2                   |    hf484d3e_1000        22.6 MB  conda-forge\n",
            "    importlib-metadata-4.8.1   |   py36h5fab9bb_0          32 KB  conda-forge\n",
            "    intel-openmp-2021.3.0      |    h06a4308_3350         1.4 MB\n",
            "    joblib-1.0.1               |     pyhd8ed1ab_0         206 KB  conda-forge\n",
            "    jpeg-9d                    |       h36c2ea0_0         264 KB  conda-forge\n",
            "    lcms2-2.11                 |       hcbb858e_1         434 KB  conda-forge\n",
            "    libblas-3.8.0              |           14_mkl          10 KB  conda-forge\n",
            "    libboost-1.67.0            |       h46d08c1_4        13.0 MB\n",
            "    libcblas-3.8.0             |           14_mkl          10 KB  conda-forge\n",
            "    libffi-3.2.1               |    he1b5a44_1007          47 KB  conda-forge\n",
            "    libgfortran-ng-7.5.0       |      h14aa051_19          22 KB  conda-forge\n",
            "    libgfortran4-7.5.0         |      h14aa051_19         1.3 MB  conda-forge\n",
            "    libglib-2.66.3             |       hbe7bbb4_0         3.0 MB  conda-forge\n",
            "    libiconv-1.16              |       h516909a_0         1.4 MB  conda-forge\n",
            "    liblapack-3.8.0            |           14_mkl          10 KB  conda-forge\n",
            "    libpng-1.6.37              |       h21135ba_2         306 KB  conda-forge\n",
            "    libprotobuf-3.13.0.1       |       h8b12597_0         2.3 MB  conda-forge\n",
            "    libtiff-4.1.0              |       hc3755c2_3         568 KB  conda-forge\n",
            "    libuuid-2.32.1             |    h14c3975_1000          26 KB  conda-forge\n",
            "    libxcb-1.13                |    h14c3975_1002         396 KB  conda-forge\n",
            "    libxml2-2.9.9              |       h13577e0_2         1.3 MB  conda-forge\n",
            "    lz4-c-1.9.2                |       he1b5a44_3         203 KB  conda-forge\n",
            "    markdown-3.3.4             |     pyhd8ed1ab_0          67 KB  conda-forge\n",
            "    mkl-2019.4                 |              243       131.2 MB\n",
            "    mkl-service-2.3.0          |   py36h516909a_0          64 KB  conda-forge\n",
            "    mkl_fft-1.1.0              |   py36hc1659b7_1         173 KB  conda-forge\n",
            "    mkl_random-1.1.0           |   py36hb3f55d8_0         366 KB  conda-forge\n",
            "    ninja-1.10.1               |       hfc4b9b4_2         1.9 MB  conda-forge\n",
            "    numpy-1.16.4               |   py36h7e9f1db_0          48 KB\n",
            "    numpy-base-1.16.4          |   py36hde5b4d6_0         3.5 MB\n",
            "    olefile-0.46               |     pyh9f0ad1d_1          32 KB  conda-forge\n",
            "    openssl-1.1.1g             |       h516909a_0         2.1 MB  rmg\n",
            "    pandas-0.25.0              |   py36hb3f55d8_0        11.4 MB  conda-forge\n",
            "    pcre-8.44                  |       he1b5a44_0         261 KB  conda-forge\n",
            "    pillow-8.0.1               |   py36h10ecd5c_0         687 KB  conda-forge\n",
            "    pip-21.2.4                 |     pyhd8ed1ab_0         1.1 MB  conda-forge\n",
            "    pixman-0.38.0              |    h516909a_1003         594 KB  conda-forge\n",
            "    protobuf-3.13.0.1          |   py36h201607c_1         696 KB  conda-forge\n",
            "    pthread-stubs-0.4          |    h36c2ea0_1001           5 KB  conda-forge\n",
            "    py-boost-1.67.0            |   py36h04863e7_4         278 KB\n",
            "    pycosat-0.6.3              |py36he6145b8_1005         107 KB  conda-forge\n",
            "    pysocks-1.7.1              |   py36h9f0ad1d_1          27 KB  rmg\n",
            "    python-3.6.8               |       h0371630_0        30.1 MB\n",
            "    python-dateutil-2.8.2      |     pyhd8ed1ab_0         240 KB  conda-forge\n",
            "    python_abi-3.6             |          2_cp36m           4 KB  conda-forge\n",
            "    pytorch-1.1.0              |py3.6_cuda9.0.176_cudnn7.5.1_0       377.0 MB  pytorch\n",
            "    pytz-2021.1                |     pyhd8ed1ab_0         239 KB  conda-forge\n",
            "    rdkit-2019.03.4.0          |   py36hc20afe1_1        23.4 MB  rdkit\n",
            "    ruamel_yaml-0.15.80        |py36he6145b8_1003         250 KB  conda-forge\n",
            "    scikit-learn-0.21.2        |   py36hcdab131_1         6.7 MB  conda-forge\n",
            "    scipy-1.3.0                |   py36h921218d_1        18.9 MB  conda-forge\n",
            "    setuptools-58.0.2          |   py36h5fab9bb_0         961 KB  conda-forge\n",
            "    six-1.16.0                 |     pyh6c4a22f_0          14 KB  conda-forge\n",
            "    tensorboard-1.13.1         |           py36_0         3.3 MB  conda-forge\n",
            "    torchvision-0.3.0          | py36_cu9.0.176_1         3.7 MB  pytorch\n",
            "    tqdm-4.32.1                |             py_0          41 KB  conda-forge\n",
            "    typing-3.6.4               |           py36_0          45 KB  conda-forge\n",
            "    typing_extensions-3.10.0.0 |     pyha770c72_0          28 KB  conda-forge\n",
            "    werkzeug-2.0.1             |     pyhd8ed1ab_0         219 KB  conda-forge\n",
            "    xorg-kbproto-1.0.7         |    h14c3975_1002          26 KB  conda-forge\n",
            "    xorg-libice-1.0.10         |       h516909a_0          57 KB  conda-forge\n",
            "    xorg-libsm-1.2.3           |    h84519dc_1000          25 KB  conda-forge\n",
            "    xorg-libx11-1.6.12         |       h36c2ea0_0         919 KB  conda-forge\n",
            "    xorg-libxau-1.0.9          |       h14c3975_0          13 KB  conda-forge\n",
            "    xorg-libxdmcp-1.1.3        |       h516909a_0          18 KB  conda-forge\n",
            "    xorg-libxext-1.3.4         |       h516909a_0          51 KB  conda-forge\n",
            "    xorg-libxrender-0.9.10     |    h516909a_1002          31 KB  conda-forge\n",
            "    xorg-renderproto-0.11.1    |    h14c3975_1002           8 KB  conda-forge\n",
            "    xorg-xextproto-7.3.0       |    h14c3975_1002          27 KB  conda-forge\n",
            "    xorg-xproto-7.0.31         |    h14c3975_1007          72 KB  conda-forge\n",
            "    zipp-3.5.0                 |     pyhd8ed1ab_0          12 KB  conda-forge\n",
            "    zstd-1.4.5                 |       h6597ccf_2         712 KB  conda-forge\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:       940.9 MB\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  blas               conda-forge/linux-64::blas-1.0-mkl\n",
            "  boost              conda-forge/linux-64::boost-1.68.0-py36h8619c78_1001\n",
            "  boost-cpp          conda-forge/linux-64::boost-cpp-1.68.0-h11c811c_1000\n",
            "  bzip2              conda-forge/linux-64::bzip2-1.0.8-h516909a_3\n",
            "  cairo              conda-forge/linux-64::cairo-1.16.0-h18b612c_1001\n",
            "  cudatoolkit        pkgs/main/linux-64::cudatoolkit-9.0-h13b8566_0\n",
            "  dataclasses        conda-forge/noarch::dataclasses-0.8-pyh787bdff_2\n",
            "  descriptastorus    rmg/noarch::descriptastorus-2.2.0-py_0\n",
            "  fontconfig         conda-forge/linux-64::fontconfig-2.13.1-he4413a7_1000\n",
            "  freetype           conda-forge/linux-64::freetype-2.10.4-h7ca028e_0\n",
            "  gettext            conda-forge/linux-64::gettext-0.19.8.1-hf34092f_1004\n",
            "  glib               conda-forge/linux-64::glib-2.66.3-h58526e2_0\n",
            "  icu                conda-forge/linux-64::icu-58.2-hf484d3e_1000\n",
            "  importlib-metadata conda-forge/linux-64::importlib-metadata-4.8.1-py36h5fab9bb_0\n",
            "  intel-openmp       pkgs/main/linux-64::intel-openmp-2021.3.0-h06a4308_3350\n",
            "  joblib             conda-forge/noarch::joblib-1.0.1-pyhd8ed1ab_0\n",
            "  jpeg               conda-forge/linux-64::jpeg-9d-h36c2ea0_0\n",
            "  lcms2              conda-forge/linux-64::lcms2-2.11-hcbb858e_1\n",
            "  libblas            conda-forge/linux-64::libblas-3.8.0-14_mkl\n",
            "  libboost           pkgs/main/linux-64::libboost-1.67.0-h46d08c1_4\n",
            "  libcblas           conda-forge/linux-64::libcblas-3.8.0-14_mkl\n",
            "  libgfortran-ng     conda-forge/linux-64::libgfortran-ng-7.5.0-h14aa051_19\n",
            "  libgfortran4       conda-forge/linux-64::libgfortran4-7.5.0-h14aa051_19\n",
            "  libglib            conda-forge/linux-64::libglib-2.66.3-hbe7bbb4_0\n",
            "  libiconv           conda-forge/linux-64::libiconv-1.16-h516909a_0\n",
            "  liblapack          conda-forge/linux-64::liblapack-3.8.0-14_mkl\n",
            "  libpng             conda-forge/linux-64::libpng-1.6.37-h21135ba_2\n",
            "  libprotobuf        conda-forge/linux-64::libprotobuf-3.13.0.1-h8b12597_0\n",
            "  libtiff            conda-forge/linux-64::libtiff-4.1.0-hc3755c2_3\n",
            "  libuuid            conda-forge/linux-64::libuuid-2.32.1-h14c3975_1000\n",
            "  libxcb             conda-forge/linux-64::libxcb-1.13-h14c3975_1002\n",
            "  libxml2            conda-forge/linux-64::libxml2-2.9.9-h13577e0_2\n",
            "  lz4-c              conda-forge/linux-64::lz4-c-1.9.2-he1b5a44_3\n",
            "  markdown           conda-forge/noarch::markdown-3.3.4-pyhd8ed1ab_0\n",
            "  mkl                pkgs/main/linux-64::mkl-2019.4-243\n",
            "  mkl-service        conda-forge/linux-64::mkl-service-2.3.0-py36h516909a_0\n",
            "  mkl_fft            conda-forge/linux-64::mkl_fft-1.1.0-py36hc1659b7_1\n",
            "  mkl_random         conda-forge/linux-64::mkl_random-1.1.0-py36hb3f55d8_0\n",
            "  ninja              conda-forge/linux-64::ninja-1.10.1-hfc4b9b4_2\n",
            "  numpy              pkgs/main/linux-64::numpy-1.16.4-py36h7e9f1db_0\n",
            "  numpy-base         pkgs/main/linux-64::numpy-base-1.16.4-py36hde5b4d6_0\n",
            "  olefile            conda-forge/noarch::olefile-0.46-pyh9f0ad1d_1\n",
            "  pandas             conda-forge/linux-64::pandas-0.25.0-py36hb3f55d8_0\n",
            "  pcre               conda-forge/linux-64::pcre-8.44-he1b5a44_0\n",
            "  pillow             conda-forge/linux-64::pillow-8.0.1-py36h10ecd5c_0\n",
            "  pixman             conda-forge/linux-64::pixman-0.38.0-h516909a_1003\n",
            "  protobuf           conda-forge/linux-64::protobuf-3.13.0.1-py36h201607c_1\n",
            "  pthread-stubs      conda-forge/linux-64::pthread-stubs-0.4-h36c2ea0_1001\n",
            "  py-boost           pkgs/main/linux-64::py-boost-1.67.0-py36h04863e7_4\n",
            "  python-dateutil    conda-forge/noarch::python-dateutil-2.8.2-pyhd8ed1ab_0\n",
            "  python_abi         conda-forge/linux-64::python_abi-3.6-2_cp36m\n",
            "  pytorch            pytorch/linux-64::pytorch-1.1.0-py3.6_cuda9.0.176_cudnn7.5.1_0\n",
            "  pytz               conda-forge/noarch::pytz-2021.1-pyhd8ed1ab_0\n",
            "  rdkit              rdkit/linux-64::rdkit-2019.03.4.0-py36hc20afe1_1\n",
            "  scikit-learn       conda-forge/linux-64::scikit-learn-0.21.2-py36hcdab131_1\n",
            "  scipy              conda-forge/linux-64::scipy-1.3.0-py36h921218d_1\n",
            "  tensorboard        conda-forge/linux-64::tensorboard-1.13.1-py36_0\n",
            "  torchvision        pytorch/linux-64::torchvision-0.3.0-py36_cu9.0.176_1\n",
            "  typing             conda-forge/linux-64::typing-3.6.4-py36_0\n",
            "  typing_extensions  conda-forge/noarch::typing_extensions-3.10.0.0-pyha770c72_0\n",
            "  werkzeug           conda-forge/noarch::werkzeug-2.0.1-pyhd8ed1ab_0\n",
            "  xorg-kbproto       conda-forge/linux-64::xorg-kbproto-1.0.7-h14c3975_1002\n",
            "  xorg-libice        conda-forge/linux-64::xorg-libice-1.0.10-h516909a_0\n",
            "  xorg-libsm         conda-forge/linux-64::xorg-libsm-1.2.3-h84519dc_1000\n",
            "  xorg-libx11        conda-forge/linux-64::xorg-libx11-1.6.12-h36c2ea0_0\n",
            "  xorg-libxau        conda-forge/linux-64::xorg-libxau-1.0.9-h14c3975_0\n",
            "  xorg-libxdmcp      conda-forge/linux-64::xorg-libxdmcp-1.1.3-h516909a_0\n",
            "  xorg-libxext       conda-forge/linux-64::xorg-libxext-1.3.4-h516909a_0\n",
            "  xorg-libxrender    conda-forge/linux-64::xorg-libxrender-0.9.10-h516909a_1002\n",
            "  xorg-renderproto   conda-forge/linux-64::xorg-renderproto-0.11.1-h14c3975_1002\n",
            "  xorg-xextproto     conda-forge/linux-64::xorg-xextproto-7.3.0-h14c3975_1002\n",
            "  xorg-xproto        conda-forge/linux-64::xorg-xproto-7.0.31-h14c3975_1007\n",
            "  zipp               conda-forge/noarch::zipp-3.5.0-pyhd8ed1ab_0\n",
            "  zstd               conda-forge/linux-64::zstd-1.4.5-h6597ccf_2\n",
            "\n",
            "The following packages will be UPDATED:\n",
            "\n",
            "  cffi                pkgs/main::cffi-1.14.3-py37h261ae71_2 --> conda-forge::cffi-1.14.4-py36h211aa47_0\n",
            "  chardet            pkgs/main::chardet-3.0.4-py37h06a4308~ --> rmg::chardet-3.0.4-py36h9f0ad1d_1006\n",
            "  conda               pkgs/main::conda-4.9.2-py37h06a4308_0 --> conda-forge::conda-4.10.3-py36h5fab9bb_0\n",
            "  pip                pkgs/main/linux-64::pip-20.2.4-py37h0~ --> conda-forge/noarch::pip-21.2.4-pyhd8ed1ab_0\n",
            "  pycosat            pkgs/main::pycosat-0.6.3-py37h27cfd23~ --> conda-forge::pycosat-0.6.3-py36he6145b8_1005\n",
            "  setuptools         pkgs/main::setuptools-50.3.1-py37h06a~ --> conda-forge::setuptools-58.0.2-py36h5fab9bb_0\n",
            "  six                pkgs/main/linux-64::six-1.15.0-py37h0~ --> conda-forge/noarch::six-1.16.0-pyh6c4a22f_0\n",
            "\n",
            "The following packages will be SUPERSEDED by a higher-priority channel:\n",
            "\n",
            "  brotlipy           pkgs/main::brotlipy-0.7.0-py37h27cfd2~ --> rmg::brotlipy-0.7.0-py36h8c4c3a4_1000\n",
            "  ca-certificates    pkgs/main::ca-certificates-2020.10.14~ --> rmg::ca-certificates-2020.6.20-hecda079_0\n",
            "  certifi            pkgs/main/noarch::certifi-2020.6.20-p~ --> rmg/linux-64::certifi-2020.6.20-py36h9f0ad1d_0\n",
            "  conda-package-han~ pkgs/main::conda-package-handling-1.7~ --> conda-forge::conda-package-handling-1.7.2-py36he6145b8_0\n",
            "  cryptography       pkgs/main::cryptography-3.2.1-py37h3c~ --> rmg::cryptography-2.9.2-py36h45558ae_0\n",
            "  libffi                   pkgs/main::libffi-3.3-he6710b0_2 --> conda-forge::libffi-3.2.1-he1b5a44_1007\n",
            "  openssl              pkgs/main::openssl-1.1.1h-h7b6447c_0 --> rmg::openssl-1.1.1g-h516909a_0\n",
            "  pysocks                   pkgs/main::pysocks-1.7.1-py37_1 --> rmg::pysocks-1.7.1-py36h9f0ad1d_1\n",
            "  ruamel_yaml        pkgs/main::ruamel_yaml-0.15.87-py37h7~ --> conda-forge::ruamel_yaml-0.15.80-py36he6145b8_1003\n",
            "  tqdm                  pkgs/main::tqdm-4.51.0-pyhd3eb1b0_0 --> conda-forge::tqdm-4.32.1-py_0\n",
            "\n",
            "The following packages will be DOWNGRADED:\n",
            "\n",
            "  python                                   3.7.9-h7579374_0 --> 3.6.8-h0371630_0\n",
            "  readline                                   8.0-h7b6447c_0 --> 7.0-h7b6447c_5\n",
            "\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages\n",
            "six-1.16.0           | 14 KB     | : 100% 1.0/1 [00:00<00:00, 10.68it/s]\n",
            "libtiff-4.1.0        | 568 KB    | : 100% 1.0/1 [00:00<00:00,  6.73it/s]\n",
            "scipy-1.3.0          | 18.9 MB   | : 100% 1.0/1 [00:05<00:00,  5.59s/it]               \n",
            "libprotobuf-3.13.0.1 | 2.3 MB    | : 100% 1.0/1 [00:00<00:00,  2.03it/s]\n",
            "importlib-metadata-4 | 32 KB     | : 100% 1.0/1 [00:00<00:00, 23.37it/s]\n",
            "markdown-3.3.4       | 67 KB     | : 100% 1.0/1 [00:00<00:00, 20.13it/s]\n",
            "mkl-service-2.3.0    | 64 KB     | : 100% 1.0/1 [00:00<00:00,  3.19it/s]                \n",
            "libpng-1.6.37        | 306 KB    | : 100% 1.0/1 [00:00<00:00, 12.93it/s]\n",
            "mkl_random-1.1.0     | 366 KB    | : 100% 1.0/1 [00:00<00:00,  2.83it/s]                \n",
            "pytz-2021.1          | 239 KB    | : 100% 1.0/1 [00:00<00:00,  7.19it/s]\n",
            "conda-package-handli | 925 KB    | : 100% 1.0/1 [00:00<00:00,  2.01it/s]\n",
            "typing_extensions-3. | 28 KB     | : 100% 1.0/1 [00:00<00:00, 12.13it/s]\n",
            "bzip2-1.0.8          | 398 KB    | : 100% 1.0/1 [00:00<00:00,  9.48it/s]\n",
            "numpy-1.16.4         | 48 KB     | : 100% 1.0/1 [00:00<00:00,  2.54it/s]               \n",
            "pycosat-0.6.3        | 107 KB    | : 100% 1.0/1 [00:00<00:00,  3.32it/s]                \n",
            "descriptastorus-2.2. | 63 KB     | : 100% 1.0/1 [00:02<00:00,  2.43s/it]\n",
            "mkl-2019.4           | 131.2 MB  | : 100% 1.0/1 [00:05<00:00,  5.38s/it]               \n",
            "cryptography-2.9.2   | 613 KB    | : 100% 1.0/1 [00:03<00:00,  3.30s/it]\n",
            "cffi-1.14.4          | 224 KB    | : 100% 1.0/1 [00:00<00:00,  9.28it/s]\n",
            "xorg-libxrender-0.9. | 31 KB     | : 100% 1.0/1 [00:00<00:00, 21.08it/s]\n",
            "certifi-2020.6.20    | 151 KB    | : 100% 1.0/1 [00:02<00:00,  2.72s/it]\n",
            "lcms2-2.11           | 434 KB    | : 100% 1.0/1 [00:00<00:00, 10.11it/s]\n",
            "pysocks-1.7.1        | 27 KB     | : 100% 1.0/1 [00:01<00:00,  1.52s/it]\n",
            "brotlipy-0.7.0       | 346 KB    | : 100% 1.0/1 [00:02<00:00,  2.22s/it]\n",
            "xorg-kbproto-1.0.7   | 26 KB     | : 100% 1.0/1 [00:00<00:00,  3.50it/s]               \n",
            "intel-openmp-2021.3. | 1.4 MB    | : 100% 1.0/1 [00:00<00:00,  6.76it/s]\n",
            "protobuf-3.13.0.1    | 696 KB    | : 100% 1.0/1 [00:00<00:00,  2.08it/s]\n",
            "xorg-libice-1.0.10   | 57 KB     | : 100% 1.0/1 [00:00<00:00, 23.99it/s]\n",
            "python-dateutil-2.8. | 240 KB    | : 100% 1.0/1 [00:00<00:00, 13.73it/s]\n",
            "libgfortran4-7.5.0   | 1.3 MB    | : 100% 1.0/1 [00:00<00:00,  3.78it/s]\n",
            "py-boost-1.67.0      | 278 KB    | : 100% 1.0/1 [00:00<00:00,  2.58it/s]\n",
            "pthread-stubs-0.4    | 5 KB      | : 100% 1.0/1 [00:00<00:00, 33.98it/s]\n",
            "torchvision-0.3.0    | 3.7 MB    | : 100% 1.0/1 [00:03<00:00,  3.13s/it]\n",
            "fontconfig-2.13.1    | 327 KB    | : 100% 1.0/1 [00:00<00:00, 10.03it/s]\n",
            "tensorboard-1.13.1   | 3.3 MB    | : 100% 1.0/1 [00:01<00:00,  1.83s/it]\n",
            "xorg-libxext-1.3.4   | 51 KB     | : 100% 1.0/1 [00:00<00:00, 21.12it/s]\n",
            "setuptools-58.0.2    | 961 KB    | : 100% 1.0/1 [00:00<00:00,  3.82it/s]\n",
            "pip-21.2.4           | 1.1 MB    | : 100% 1.0/1 [00:00<00:00,  3.52it/s]\n",
            "pixman-0.38.0        | 594 KB    | : 100% 1.0/1 [00:00<00:00,  7.73it/s]\n",
            "zipp-3.5.0           | 12 KB     | : 100% 1.0/1 [00:00<00:00, 32.33it/s]\n",
            "libboost-1.67.0      | 13.0 MB   | : 100% 1.0/1 [00:02<00:00,  2.48s/it]\n",
            "libiconv-1.16        | 1.4 MB    | : 100% 1.0/1 [00:00<00:00,  3.89it/s]\n",
            "gettext-0.19.8.1     | 3.6 MB    | : 100% 1.0/1 [00:00<00:00,  1.09it/s]\n",
            "olefile-0.46         | 32 KB     | : 100% 1.0/1 [00:00<00:00, 27.73it/s]\n",
            "werkzeug-2.0.1       | 219 KB    | : 100% 1.0/1 [00:00<00:00, 13.37it/s]\n",
            "python_abi-3.6       | 4 KB      | : 100% 1.0/1 [00:00<00:00, 33.59it/s]\n",
            "libgfortran-ng-7.5.0 | 22 KB     | : 100% 1.0/1 [00:00<00:00, 28.41it/s]\n",
            "libxml2-2.9.9        | 1.3 MB    | : 100% 1.0/1 [00:00<00:00,  1.53it/s]\n",
            "jpeg-9d              | 264 KB    | : 100% 1.0/1 [00:00<00:00, 12.01it/s]\n",
            "xorg-libsm-1.2.3     | 25 KB     | : 100% 1.0/1 [00:00<00:00, 32.67it/s]\n",
            "xorg-libxau-1.0.9    | 13 KB     | : 100% 1.0/1 [00:00<00:00, 33.10it/s]\n",
            "openssl-1.1.1g       | 2.1 MB    | : 100% 1.0/1 [00:03<00:00,  3.99s/it]\n",
            "conda-4.10.3         | 3.1 MB    | : 100% 1.0/1 [00:00<00:00,  1.61it/s]\n",
            "xorg-libxdmcp-1.1.3  | 18 KB     | : 100% 1.0/1 [00:00<00:00,  3.49it/s]               \n",
            "pcre-8.44            | 261 KB    | : 100% 1.0/1 [00:00<00:00, 12.94it/s]\n",
            "numpy-base-1.16.4    | 3.5 MB    | : 100% 1.0/1 [00:00<00:00,  1.04it/s]\n",
            "cairo-1.16.0         | 1.5 MB    | : 100% 1.0/1 [00:00<00:00,  1.09it/s]               \n",
            "typing-3.6.4         | 45 KB     | : 100% 1.0/1 [00:00<00:00,  3.31it/s]                \n",
            "scikit-learn-0.21.2  | 6.7 MB    | : 100% 1.0/1 [00:02<00:00,  2.56s/it]\n",
            "xorg-xproto-7.0.31   | 72 KB     | : 100% 1.0/1 [00:00<00:00,  3.16it/s]                \n",
            "xorg-xextproto-7.3.0 | 27 KB     | : 100% 1.0/1 [00:00<00:00, 24.32it/s]\n",
            "ruamel_yaml-0.15.80  | 250 KB    | : 100% 1.0/1 [00:00<00:00,  2.70it/s]                \n",
            "libblas-3.8.0        | 10 KB     | : 100% 1.0/1 [00:00<00:00,  3.61it/s]\n",
            "python-3.6.8         | 30.1 MB   | : 100% 1.0/1 [00:01<00:00,  1.13s/it]               \n",
            "libuuid-2.32.1       | 26 KB     | : 100% 1.0/1 [00:00<00:00, 27.19it/s]\n",
            "ninja-1.10.1         | 1.9 MB    | : 100% 1.0/1 [00:01<00:00,  1.07s/it]\n",
            "glib-2.66.3          | 500 KB    | : 100% 1.0/1 [00:00<00:00,  5.53it/s]\n",
            "libxcb-1.13          | 396 KB    | : 100% 1.0/1 [00:00<00:00,  2.41it/s]\n",
            "ca-certificates-2020 | 145 KB    | : 100% 1.0/1 [00:02<00:00,  2.08s/it]\n",
            "chardet-3.0.4        | 188 KB    | : 100% 1.0/1 [00:02<00:00,  2.80s/it]\n",
            "cudatoolkit-9.0      | 237.0 MB  | : 100% 1.0/1 [00:06<00:00,  6.51s/it]               \n",
            "tqdm-4.32.1          | 41 KB     | : 100% 1.0/1 [00:00<00:00,  3.22it/s]               \n",
            "boost-cpp-1.68.0     | 20.5 MB   | : 100% 1.0/1 [00:09<00:00,  9.27s/it]               \n",
            "lz4-c-1.9.2          | 203 KB    | : 100% 1.0/1 [00:00<00:00, 14.14it/s]\n",
            "libcblas-3.8.0       | 10 KB     | : 100% 1.0/1 [00:00<00:00,  3.29it/s]\n",
            "libglib-2.66.3       | 3.0 MB    | : 100% 1.0/1 [00:00<00:00,  1.58it/s]\n",
            "liblapack-3.8.0      | 10 KB     | : 100% 1.0/1 [00:00<00:00,  3.56it/s]\n",
            "dataclasses-0.8      | 22 KB     | : 100% 1.0/1 [00:00<00:00, 28.62it/s]\n",
            "joblib-1.0.1         | 206 KB    | : 100% 1.0/1 [00:00<00:00, 11.47it/s]\n",
            "pytorch-1.1.0        | 377.0 MB  | : 100% 1.0/1 [01:17<00:00, 77.57s/it]               \n",
            "pillow-8.0.1         | 687 KB    | : 100% 1.0/1 [00:00<00:00,  2.32it/s]\n",
            "zstd-1.4.5           | 712 KB    | : 100% 1.0/1 [00:00<00:00,  7.28it/s]\n",
            "boost-1.68.0         | 325 KB    | : 100% 1.0/1 [00:00<00:00,  2.57it/s]\n",
            "xorg-libx11-1.6.12   | 919 KB    | : 100% 1.0/1 [00:00<00:00,  1.77it/s]\n",
            "libffi-3.2.1         | 47 KB     | : 100% 1.0/1 [00:00<00:00, 16.41it/s]\n",
            "freetype-2.10.4      | 912 KB    | : 100% 1.0/1 [00:00<00:00,  5.41it/s]\n",
            "blas-1.0             | 1 KB      | : 100% 1.0/1 [00:00<00:00, 25.89it/s]\n",
            "pandas-0.25.0        | 11.4 MB   | : 100% 1.0/1 [00:04<00:00,  4.44s/it]               \n",
            "xorg-renderproto-0.1 | 8 KB      | : 100% 1.0/1 [00:00<00:00, 26.65it/s]\n",
            "mkl_fft-1.1.0        | 173 KB    | : 100% 1.0/1 [00:00<00:00,  2.85it/s]                \n",
            "icu-58.2             | 22.6 MB   | : 100% 1.0/1 [00:03<00:00,  3.54s/it]\n",
            "rdkit-2019.03.4.0    | 23.4 MB   | : 100% 1.0/1 [00:09<00:00,  9.69s/it]\n",
            "Preparing transaction: | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "Verifying transaction: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
            "Executing transaction: - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q44nhh9ulfT2",
        "outputId": "43e3381c-a5f8-4f1e-c702-6c7f355c409a"
      },
      "source": [
        "!python grover/scripts/save_features.py --data_path grover/exampledata/pretrain/tryout.csv  \\\n",
        "                                --save_path grover/exampledata/pretrain/tryout.npz   \\\n",
        "                                --features_generator fgtasklabel \\\n",
        "                                --restart"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "100% 5970/5970 [00:16<00:00, 365.78it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UXkrZV4nlg74",
        "outputId": "da2c3129-04b7-4253-8244-b6d74dbc2f30"
      },
      "source": [
        "!python grover/scripts/build_vocab.py --data_path grover/exampledata/pretrain/tryout.csv  \\\n",
        "                             --vocab_save_folder grover/exampledata/pretrain  \\\n",
        "                             --dataset_name tryout"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Building atom vocab from file: grover/exampledata/pretrain/tryout.csv\n",
            "50000it [00:05, 9123.83it/s]\n",
            "atom vocab size 324\n",
            "Building bond vocab from file: grover/exampledata/pretrain/tryout.csv\n",
            "50000it [00:22, 2230.64it/s]bond vocab size 353\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-YLUGQ6Fn_Hb",
        "outputId": "cf4c936c-992d-486c-9fc4-5fcbeedf933b"
      },
      "source": [
        "from google.colab import drive\n",
        "!mkdir mount_drive\n",
        "drive.mount('mount_drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at mount_drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fyybF14Foyic",
        "outputId": "1e21eb82-a9d2-40ba-ba47-f1bc5008cd12"
      },
      "source": [
        "!python grover/scripts/save_features.py --data_path grover/exampledata/finetune/bbbp.csv \\\n",
        "                                --save_path grover/exampledata/finetune/bbbp.npz \\\n",
        "                                --features_generator rdkit_2d_normalized \\\n",
        "                                --restart "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:11] WARNING: not removing hydrogen atom without neighbors\n",
            "  1% 14/2039 [00:02<18:36,  1.81it/s][04:52:14] WARNING: not removing hydrogen atom without neighbors\n",
            "  2% 48/2039 [00:03<05:19,  6.23it/s][04:52:15] WARNING: not removing hydrogen atom without neighbors\n",
            "  5% 94/2039 [00:06<03:23,  9.55it/s][04:52:18] WARNING: not removing hydrogen atom without neighbors\n",
            "  6% 121/2039 [00:07<02:00, 15.87it/s][04:52:19] WARNING: not removing hydrogen atom without neighbors\n",
            "  8% 156/2039 [00:08<02:18, 13.58it/s][04:52:21] WARNING: not removing hydrogen atom without neighbors\n",
            "  8% 159/2039 [00:09<02:25, 12.90it/s][04:52:22] WARNING: not removing hydrogen atom without neighbors\n",
            "  8% 169/2039 [00:10<03:02, 10.27it/s][04:52:22] WARNING: not removing hydrogen atom without neighbors\n",
            " 10% 198/2039 [00:11<01:34, 19.50it/s][04:52:23] WARNING: not removing hydrogen atom without neighbors\n",
            " 13% 267/2039 [00:14<02:31, 11.68it/s][04:52:27] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:27] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:27] WARNING: not removing hydrogen atom without neighbors\n",
            " 15% 303/2039 [00:16<01:19, 21.74it/s][04:52:28] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:28] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:28] WARNING: not removing hydrogen atom without neighbors\n",
            " 18% 369/2039 [00:19<02:53,  9.65it/s][04:52:33] WARNING: not removing hydrogen atom without neighbors\n",
            " 18% 372/2039 [00:22<08:19,  3.34it/s][04:52:35] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:35] WARNING: not removing hydrogen atom without neighbors\n",
            " 23% 464/2039 [00:24<03:00,  8.74it/s][04:52:36] WARNING: not removing hydrogen atom without neighbors\n",
            " 26% 528/2039 [00:27<01:25, 17.74it/s][04:52:39] WARNING: not removing hydrogen atom without neighbors\n",
            " 27% 551/2039 [00:28<01:18, 19.06it/s][04:52:40] WARNING: not removing hydrogen atom without neighbors\n",
            " 28% 570/2039 [00:29<01:34, 15.51it/s][04:52:41] WARNING: not removing hydrogen atom without neighbors\n",
            " 29% 594/2039 [00:30<02:11, 11.00it/s][04:52:42] WARNING: not removing hydrogen atom without neighbors\n",
            " 30% 618/2039 [00:31<01:31, 15.58it/s][04:52:43] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:43] WARNING: not removing hydrogen atom without neighbors\n",
            " 32% 644/2039 [00:33<01:38, 14.09it/s][04:52:45] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:52:45] WARNING: not removing hydrogen atom without neighbors\n",
            " 34% 687/2039 [00:35<01:41, 13.37it/s][04:52:47] WARNING: not removing hydrogen atom without neighbors\n",
            " 35% 714/2039 [00:37<02:11, 10.08it/s][04:52:49] WARNING: not removing hydrogen atom without neighbors\n",
            " 39% 794/2039 [00:41<01:34, 13.14it/s][04:52:55] WARNING: not removing hydrogen atom without neighbors\n",
            " 39% 802/2039 [00:43<03:09,  6.54it/s][04:52:56] WARNING: not removing hydrogen atom without neighbors\n",
            " 44% 897/2039 [00:47<01:36, 11.84it/s][04:52:59] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:53:00] WARNING: not removing hydrogen atom without neighbors\n",
            " 44% 906/2039 [00:48<01:51, 10.19it/s][04:53:01] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:53:01] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:53:01] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:53:02] WARNING: not removing hydrogen atom without neighbors\n",
            " 50% 1010/2039 [00:53<01:49,  9.44it/s][04:53:05] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:53:06] WARNING: not removing hydrogen atom without neighbors\n",
            " 56% 1134/2039 [00:59<00:46, 19.50it/s][04:53:11] WARNING: not removing hydrogen atom without neighbors\n",
            " 57% 1161/2039 [01:00<00:43, 20.05it/s][04:53:12] WARNING: not removing hydrogen atom without neighbors\n",
            " 57% 1164/2039 [01:00<00:54, 15.99it/s]04:53:12] WARNING: not removing hydrogen atom without neighbors\n",
            " 57% 1167/2039 [01:01<00:57, 15.08it/s][04:53:13] WARNING: not removing hydrogen atom without neighbors\n",
            " 58% 1184/2039 [01:01<00:42, 20.06it/s][04:53:14] WARNING: not removing hydrogen atom without neighbors\n",
            " 59% 1195/2039 [01:02<00:37, 22.54it/s][04:53:14] WARNING: not removing hydrogen atom without neighbors\n",
            " 61% 1235/2039 [01:04<00:52, 15.45it/s][04:53:16] WARNING: not removing hydrogen atom without neighbors\n",
            " 62% 1266/2039 [01:05<00:41, 18.64it/s][04:53:18] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:53:18] WARNING: not removing hydrogen atom without neighbors\n",
            " 62% 1274/2039 [01:06<00:32, 23.70it/s][04:53:18] WARNING: not removing hydrogen atom without neighbors\n",
            " 63% 1287/2039 [01:07<00:43, 17.10it/s][04:53:19] WARNING: not removing hydrogen atom without neighbors\n",
            " 63% 1291/2039 [01:07<00:40, 18.64it/s][04:53:19] WARNING: not removing hydrogen atom without neighbors\n",
            " 64% 1296/2039 [01:07<00:46, 16.10it/s][04:53:19] WARNING: not removing hydrogen atom without neighbors\n",
            " 64% 1310/2039 [01:08<00:45, 16.02it/s][04:53:20] WARNING: not removing hydrogen atom without neighbors\n",
            " 64% 1314/2039 [01:08<00:43, 16.78it/s][04:53:20] WARNING: not removing hydrogen atom without neighbors\n",
            " 65% 1334/2039 [01:09<00:38, 18.28it/s][04:53:21] WARNING: not removing hydrogen atom without neighbors\n",
            " 67% 1356/2039 [01:10<00:45, 15.07it/s][04:53:22] WARNING: not removing hydrogen atom without neighbors\n",
            " 68% 1385/2039 [01:12<00:44, 14.66it/s][04:53:24] WARNING: not removing hydrogen atom without neighbors\n",
            " 71% 1443/2039 [01:14<00:36, 16.54it/s]04:53:27] WARNING: not removing hydrogen atom without neighbors\n",
            " 71% 1449/2039 [01:15<00:39, 14.84it/s][04:53:27] WARNING: not removing hydrogen atom without neighbors\n",
            " 72% 1462/2039 [01:15<00:32, 17.79it/s][04:53:28] WARNING: not removing hydrogen atom without neighbors\n",
            " 72% 1466/2039 [01:16<00:47, 12.14it/s][04:53:28] WARNING: not removing hydrogen atom without neighbors\n",
            " 77% 1566/2039 [01:20<00:23, 20.43it/s][04:53:32] WARNING: not removing hydrogen atom without neighbors\n",
            " 78% 1588/2039 [01:21<00:23, 18.80it/s][04:53:34] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:53:34] WARNING: not removing hydrogen atom without neighbors\n",
            " 78% 1591/2039 [01:22<00:37, 12.02it/s][04:53:34] WARNING: not removing hydrogen atom without neighbors\n",
            " 79% 1610/2039 [01:23<00:25, 16.99it/s][04:53:35] WARNING: not removing hydrogen atom without neighbors\n",
            " 79% 1620/2039 [01:23<00:20, 20.11it/s][04:53:35] WARNING: not removing hydrogen atom without neighbors\n",
            " 81% 1660/2039 [01:25<00:30, 12.27it/s][04:53:37] WARNING: not removing hydrogen atom without neighbors\n",
            " 82% 1667/2039 [01:25<00:23, 15.82it/s][04:53:38] WARNING: not removing hydrogen atom without neighbors\n",
            " 83% 1687/2039 [01:27<00:24, 14.15it/s][04:53:39] WARNING: not removing hydrogen atom without neighbors\n",
            "[04:53:39] WARNING: not removing hydrogen atom without neighbors\n",
            " 83% 1690/2039 [01:27<00:29, 11.74it/s][04:53:39] WARNING: not removing hydrogen atom without neighbors\n",
            " 84% 1714/2039 [01:28<00:20, 15.92it/s][04:53:40] WARNING: not removing hydrogen atom without neighbors\n",
            " 85% 1730/2039 [01:29<00:23, 12.93it/s][04:53:41] WARNING: not removing hydrogen atom without neighbors\n",
            " 87% 1766/2039 [01:30<00:13, 20.05it/s][04:53:42] WARNING: not removing hydrogen atom without neighbors\n",
            " 87% 1772/2039 [01:31<00:15, 16.71it/s]04:53:43] WARNING: not removing hydrogen atom without neighbors\n",
            " 88% 1793/2039 [01:32<00:15, 15.46it/s][04:53:44] WARNING: not removing hydrogen atom without neighbors\n",
            " 92% 1870/2039 [01:36<00:11, 14.91it/s][04:53:48] WARNING: not removing hydrogen atom without neighbors\n",
            " 93% 1896/2039 [01:37<00:07, 18.72it/s][04:53:49] WARNING: not removing hydrogen atom without neighbors\n",
            " 95% 1941/2039 [01:39<00:06, 14.35it/s][04:53:52] WARNING: not removing hydrogen atom without neighbors\n",
            " 97% 1971/2039 [01:41<00:03, 21.16it/s][04:53:53] WARNING: not removing hydrogen atom without neighbors\n",
            "100% 2039/2039 [01:43<00:00, 19.63it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0Yl5KFAIp-wV",
        "outputId": "a02de0d4-f5a8-4bc4-c5e7-e44f1e220791"
      },
      "source": [
        "!python grover/main.py finetune --data_path grover/exampledata/finetune/bbbp.csv \\\n",
        "                        --features_path grover/exampledata/finetune/bbbp.npz \\\n",
        "                        --save_dir grover/model/finetune/bbbp/ \\\n",
        "                        --checkpoint_path /content/mount_drive/MyDrive/Dacon/saumsung_AI/grover_large.pt \\\n",
        "                        --dataset_type classification \\\n",
        "                        --split_type scaffold_balanced \\\n",
        "                        --ensemble_size 1 \\\n",
        "                        --num_folds 3 \\\n",
        "                        --no_features_scaling \\\n",
        "                        --ffn_hidden_size 200 \\\n",
        "                        --batch_size 32 \\\n",
        "                        --epochs 10 \\\n",
        "                        --init_lr 0.00015"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[WARNING] Horovod cannot be imported; multi-GPU training is unsupported\n",
            "Fold 0\n",
            "Loading data\n",
            "Number of tasks = 1\n",
            "Splitting data with seed 0\n",
            "100% 2039/2039 [00:00<00:00, 2416.36it/s]\n",
            "Total scaffolds = 1,025 | train scaffolds = 764 | val scaffolds = 123 | test scaffolds = 138\n",
            "Label averages per scaffold, in decreasing order of scaffold frequency,capped at 10 scaffolds and 20 labels: [(array([0.72992701]), array([137])), (array([1.]), array([1])), (array([0.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([0.]), array([1])), (array([1.]), array([1])), (array([1.]), array([2])), (array([0.]), array([2])), (array([1.]), array([1]))]\n",
            "Class sizes\n",
            "p_np 0: 23.49%, 1: 76.51%\n",
            "Total size = 2,039 | train size = 1,631 | val size = 203 | test size = 205\n",
            "Loading model 0 from /content/mount_drive/MyDrive/Dacon/saumsung_AI/grover_large.pt\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_node.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_edge.weight\".\n",
            "GroverFinetuneTask(\n",
            "  (grover): GROVEREmbedding(\n",
            "    (encoders): GTransEncoder(\n",
            "      (edge_blocks): ModuleList(\n",
            "        (0): MTBlock(\n",
            "          (heads): ModuleList(\n",
            "            (0): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (1): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (2): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (3): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "          )\n",
            "          (act_func): PReLU(num_parameters=1)\n",
            "          (dropout_layer): Dropout(p=0.0)\n",
            "          (layernorm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "          (W_i): Linear(in_features=165, out_features=1200, bias=False)\n",
            "          (attn): MultiHeadedAttention(\n",
            "            (linear_layers): ModuleList(\n",
            "              (0): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (1): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (2): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "            )\n",
            "            (output_linear): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "            (attention): Attention()\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "          (W_o): Linear(in_features=4800, out_features=1200, bias=False)\n",
            "          (sublayer): SublayerConnection(\n",
            "            (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "      (node_blocks): ModuleList(\n",
            "        (0): MTBlock(\n",
            "          (heads): ModuleList(\n",
            "            (0): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (1): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (2): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (3): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "          )\n",
            "          (act_func): PReLU(num_parameters=1)\n",
            "          (dropout_layer): Dropout(p=0.0)\n",
            "          (layernorm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "          (W_i): Linear(in_features=151, out_features=1200, bias=False)\n",
            "          (attn): MultiHeadedAttention(\n",
            "            (linear_layers): ModuleList(\n",
            "              (0): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (1): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (2): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "            )\n",
            "            (output_linear): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "            (attention): Attention()\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "          (W_o): Linear(in_features=4800, out_features=1200, bias=False)\n",
            "          (sublayer): SublayerConnection(\n",
            "            (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "      (ffn_atom_from_atom): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1351, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (ffn_atom_from_bond): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1351, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (ffn_bond_from_atom): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1365, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (ffn_bond_from_bond): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1365, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (atom_from_atom_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (atom_from_bond_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (bond_from_atom_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (bond_from_bond_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (act_func_node): PReLU(num_parameters=1)\n",
            "      (act_func_edge): PReLU(num_parameters=1)\n",
            "      (dropout_layer): Dropout(p=0.0)\n",
            "    )\n",
            "  )\n",
            "  (readout): Readout()\n",
            "  (mol_atom_from_atom_ffn): Sequential(\n",
            "    (0): Dropout(p=0.0)\n",
            "    (1): Linear(in_features=1400, out_features=200, bias=True)\n",
            "    (2): PReLU(num_parameters=1)\n",
            "    (3): Dropout(p=0.0)\n",
            "    (4): Linear(in_features=200, out_features=1, bias=True)\n",
            "  )\n",
            "  (mol_atom_from_bond_ffn): Sequential(\n",
            "    (0): Dropout(p=0.0)\n",
            "    (1): Linear(in_features=1400, out_features=200, bias=True)\n",
            "    (2): PReLU(num_parameters=1)\n",
            "    (3): Dropout(p=0.0)\n",
            "    (4): Linear(in_features=200, out_features=1, bias=True)\n",
            "  )\n",
            "  (sigmoid): Sigmoid()\n",
            ")\n",
            "Number of parameters = 107,704,036\n",
            "Moving model to cuda\n",
            "Epoch: 0000 loss_train: 1.098649 loss_val: 0.525451 auc_val: 0.8640 cur_lr: 0.00058 t_time: 99.9226s v_time: 4.1108s\n",
            "Epoch: 0001 loss_train: 1.104694 loss_val: 0.516855 auc_val: 0.8418 cur_lr: 0.00099 t_time: 98.2197s v_time: 4.1147s\n",
            "Epoch: 0002 loss_train: 0.941850 loss_val: 0.509589 auc_val: 0.8712 cur_lr: 0.00074 t_time: 99.0311s v_time: 4.1423s\n",
            "Epoch: 0003 loss_train: 0.870565 loss_val: 0.497164 auc_val: 0.9013 cur_lr: 0.00055 t_time: 98.3182s v_time: 4.0170s\n",
            "Epoch: 0004 loss_train: 0.814979 loss_val: 0.496561 auc_val: 0.9031 cur_lr: 0.00041 t_time: 98.7493s v_time: 4.0590s\n",
            "Epoch: 0005 loss_train: 0.773577 loss_val: 0.489164 auc_val: 0.9025 cur_lr: 0.00031 t_time: 98.4377s v_time: 4.0709s\n",
            "Epoch: 0006 loss_train: 0.735468 loss_val: 0.487518 auc_val: 0.8840 cur_lr: 0.00023 t_time: 97.9784s v_time: 4.1301s\n",
            "Epoch: 0007 loss_train: 0.714602 loss_val: 0.483080 auc_val: 0.8962 cur_lr: 0.00017 t_time: 98.0139s v_time: 4.1541s\n",
            "Epoch: 0008 loss_train: 0.701808 loss_val: 0.485183 auc_val: 0.8985 cur_lr: 0.00013 t_time: 98.8978s v_time: 4.0429s\n",
            "Epoch: 0009 loss_train: 0.681117 loss_val: 0.483437 auc_val: 0.9033 cur_lr: 0.00010 t_time: 99.4728s v_time: 4.0428s\n",
            "Model 0 best val loss = 0.483080 on epoch 7\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_node.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_edge.weight\".\n",
            "Loading pretrained parameter \"readout.cached_zero_vector\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.bias\".\n",
            "Moving model to cuda\n",
            "Model 0 test auc = 0.892672\n",
            "Ensemble test auc = 0.892672\n",
            "Fold 1\n",
            "Loading data\n",
            "Number of tasks = 1\n",
            "Splitting data with seed 1\n",
            "100% 2039/2039 [00:00<00:00, 2353.47it/s]\n",
            "Total scaffolds = 1,025 | train scaffolds = 768 | val scaffolds = 132 | test scaffolds = 125\n",
            "Label averages per scaffold, in decreasing order of scaffold frequency,capped at 10 scaffolds and 20 labels: [(array([0.72992701]), array([137])), (array([1.]), array([2])), (array([1.]), array([3])), (array([0.8]), array([5])), (array([1.]), array([9])), (array([1.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1]))]\n",
            "Class sizes\n",
            "p_np 0: 23.49%, 1: 76.51%\n",
            "Total size = 2,039 | train size = 1,631 | val size = 203 | test size = 205\n",
            "Loading model 0 from /content/mount_drive/MyDrive/Dacon/saumsung_AI/grover_large.pt\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_node.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_edge.weight\".\n",
            "GroverFinetuneTask(\n",
            "  (grover): GROVEREmbedding(\n",
            "    (encoders): GTransEncoder(\n",
            "      (edge_blocks): ModuleList(\n",
            "        (0): MTBlock(\n",
            "          (heads): ModuleList(\n",
            "            (0): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (1): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (2): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (3): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "          )\n",
            "          (act_func): PReLU(num_parameters=1)\n",
            "          (dropout_layer): Dropout(p=0.0)\n",
            "          (layernorm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "          (W_i): Linear(in_features=165, out_features=1200, bias=False)\n",
            "          (attn): MultiHeadedAttention(\n",
            "            (linear_layers): ModuleList(\n",
            "              (0): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (1): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (2): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "            )\n",
            "            (output_linear): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "            (attention): Attention()\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "          (W_o): Linear(in_features=4800, out_features=1200, bias=False)\n",
            "          (sublayer): SublayerConnection(\n",
            "            (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "      (node_blocks): ModuleList(\n",
            "        (0): MTBlock(\n",
            "          (heads): ModuleList(\n",
            "            (0): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (1): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (2): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (3): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "          )\n",
            "          (act_func): PReLU(num_parameters=1)\n",
            "          (dropout_layer): Dropout(p=0.0)\n",
            "          (layernorm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "          (W_i): Linear(in_features=151, out_features=1200, bias=False)\n",
            "          (attn): MultiHeadedAttention(\n",
            "            (linear_layers): ModuleList(\n",
            "              (0): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (1): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (2): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "            )\n",
            "            (output_linear): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "            (attention): Attention()\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "          (W_o): Linear(in_features=4800, out_features=1200, bias=False)\n",
            "          (sublayer): SublayerConnection(\n",
            "            (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "      (ffn_atom_from_atom): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1351, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (ffn_atom_from_bond): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1351, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (ffn_bond_from_atom): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1365, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (ffn_bond_from_bond): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1365, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (atom_from_atom_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (atom_from_bond_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (bond_from_atom_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (bond_from_bond_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (act_func_node): PReLU(num_parameters=1)\n",
            "      (act_func_edge): PReLU(num_parameters=1)\n",
            "      (dropout_layer): Dropout(p=0.0)\n",
            "    )\n",
            "  )\n",
            "  (readout): Readout()\n",
            "  (mol_atom_from_atom_ffn): Sequential(\n",
            "    (0): Dropout(p=0.0)\n",
            "    (1): Linear(in_features=1400, out_features=200, bias=True)\n",
            "    (2): PReLU(num_parameters=1)\n",
            "    (3): Dropout(p=0.0)\n",
            "    (4): Linear(in_features=200, out_features=1, bias=True)\n",
            "  )\n",
            "  (mol_atom_from_bond_ffn): Sequential(\n",
            "    (0): Dropout(p=0.0)\n",
            "    (1): Linear(in_features=1400, out_features=200, bias=True)\n",
            "    (2): PReLU(num_parameters=1)\n",
            "    (3): Dropout(p=0.0)\n",
            "    (4): Linear(in_features=200, out_features=1, bias=True)\n",
            "  )\n",
            "  (sigmoid): Sigmoid()\n",
            ")\n",
            "Number of parameters = 107,704,036\n",
            "Moving model to cuda\n",
            "Epoch: 0000 loss_train: 0.889967 loss_val: 0.480780 auc_val: 0.8988 cur_lr: 0.00058 t_time: 99.9517s v_time: 4.3774s\n",
            "Epoch: 0001 loss_train: 1.150994 loss_val: 0.524761 auc_val: 0.8258 cur_lr: 0.00099 t_time: 99.4987s v_time: 4.3227s\n",
            "Epoch: 0002 loss_train: 0.914500 loss_val: 0.504773 auc_val: 0.8693 cur_lr: 0.00074 t_time: 97.8741s v_time: 4.3335s\n",
            "Epoch: 0003 loss_train: 0.823986 loss_val: 0.496473 auc_val: 0.8816 cur_lr: 0.00055 t_time: 99.6927s v_time: 4.4300s\n",
            "Epoch: 0004 loss_train: 0.777720 loss_val: 0.492472 auc_val: 0.8741 cur_lr: 0.00041 t_time: 98.3380s v_time: 4.3198s\n",
            "Epoch: 0005 loss_train: 0.724094 loss_val: 0.480936 auc_val: 0.8842 cur_lr: 0.00031 t_time: 99.4301s v_time: 4.3442s\n",
            "Epoch: 0006 loss_train: 0.716994 loss_val: 0.480552 auc_val: 0.8812 cur_lr: 0.00023 t_time: 98.4684s v_time: 4.4299s\n",
            "Epoch: 0007 loss_train: 0.692097 loss_val: 0.476054 auc_val: 0.8945 cur_lr: 0.00017 t_time: 98.9413s v_time: 4.2855s\n",
            "Epoch: 0008 loss_train: 0.680352 loss_val: 0.475212 auc_val: 0.8990 cur_lr: 0.00013 t_time: 98.8385s v_time: 4.3457s\n",
            "Epoch: 0009 loss_train: 0.656036 loss_val: 0.475476 auc_val: 0.9036 cur_lr: 0.00010 t_time: 98.6776s v_time: 4.5478s\n",
            "Model 0 best val loss = 0.475212 on epoch 8\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.bias\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.bias\".\n",
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            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_node.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_edge.weight\".\n",
            "Loading pretrained parameter \"readout.cached_zero_vector\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.bias\".\n",
            "Moving model to cuda\n",
            "Model 0 test auc = 0.902909\n",
            "Ensemble test auc = 0.902909\n",
            "Fold 2\n",
            "Loading data\n",
            "Number of tasks = 1\n",
            "Splitting data with seed 2\n",
            "100% 2039/2039 [00:00<00:00, 2303.99it/s]\n",
            "Total scaffolds = 1,025 | train scaffolds = 766 | val scaffolds = 125 | test scaffolds = 134\n",
            "Label averages per scaffold, in decreasing order of scaffold frequency,capped at 10 scaffolds and 20 labels: [(array([0.72992701]), array([137])), (array([1.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([0.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([0.]), array([5])), (array([1.]), array([1]))]\n",
            "Class sizes\n",
            "p_np 0: 23.49%, 1: 76.51%\n",
            "Total size = 2,039 | train size = 1,631 | val size = 203 | test size = 205\n",
            "Loading model 0 from /content/mount_drive/MyDrive/Dacon/saumsung_AI/grover_large.pt\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_node.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_edge.weight\".\n",
            "GroverFinetuneTask(\n",
            "  (grover): GROVEREmbedding(\n",
            "    (encoders): GTransEncoder(\n",
            "      (edge_blocks): ModuleList(\n",
            "        (0): MTBlock(\n",
            "          (heads): ModuleList(\n",
            "            (0): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (1): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (2): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (3): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "          )\n",
            "          (act_func): PReLU(num_parameters=1)\n",
            "          (dropout_layer): Dropout(p=0.0)\n",
            "          (layernorm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "          (W_i): Linear(in_features=165, out_features=1200, bias=False)\n",
            "          (attn): MultiHeadedAttention(\n",
            "            (linear_layers): ModuleList(\n",
            "              (0): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (1): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (2): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "            )\n",
            "            (output_linear): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "            (attention): Attention()\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "          (W_o): Linear(in_features=4800, out_features=1200, bias=False)\n",
            "          (sublayer): SublayerConnection(\n",
            "            (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "      (node_blocks): ModuleList(\n",
            "        (0): MTBlock(\n",
            "          (heads): ModuleList(\n",
            "            (0): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (1): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (2): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "            (3): Head(\n",
            "              (mpn_q): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_k): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "              (mpn_v): MPNEncoder(\n",
            "                (dropout_layer): Dropout(p=0.0)\n",
            "                (act_func): PReLU(num_parameters=1)\n",
            "                (W_h): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "              )\n",
            "            )\n",
            "          )\n",
            "          (act_func): PReLU(num_parameters=1)\n",
            "          (dropout_layer): Dropout(p=0.0)\n",
            "          (layernorm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "          (W_i): Linear(in_features=151, out_features=1200, bias=False)\n",
            "          (attn): MultiHeadedAttention(\n",
            "            (linear_layers): ModuleList(\n",
            "              (0): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (1): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "              (2): Linear(in_features=1200, out_features=1200, bias=True)\n",
            "            )\n",
            "            (output_linear): Linear(in_features=1200, out_features=1200, bias=False)\n",
            "            (attention): Attention()\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "          (W_o): Linear(in_features=4800, out_features=1200, bias=False)\n",
            "          (sublayer): SublayerConnection(\n",
            "            (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "            (dropout): Dropout(p=0.0)\n",
            "          )\n",
            "        )\n",
            "      )\n",
            "      (ffn_atom_from_atom): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1351, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (ffn_atom_from_bond): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1351, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (ffn_bond_from_atom): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1365, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (ffn_bond_from_bond): PositionwiseFeedForward(\n",
            "        (W_1): Linear(in_features=1365, out_features=4800, bias=True)\n",
            "        (W_2): Linear(in_features=4800, out_features=1200, bias=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "        (act_func): PReLU(num_parameters=1)\n",
            "      )\n",
            "      (atom_from_atom_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (atom_from_bond_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (bond_from_atom_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (bond_from_bond_sublayer): SublayerConnection(\n",
            "        (norm): LayerNorm(torch.Size([1200]), eps=1e-05, elementwise_affine=True)\n",
            "        (dropout): Dropout(p=0.0)\n",
            "      )\n",
            "      (act_func_node): PReLU(num_parameters=1)\n",
            "      (act_func_edge): PReLU(num_parameters=1)\n",
            "      (dropout_layer): Dropout(p=0.0)\n",
            "    )\n",
            "  )\n",
            "  (readout): Readout()\n",
            "  (mol_atom_from_atom_ffn): Sequential(\n",
            "    (0): Dropout(p=0.0)\n",
            "    (1): Linear(in_features=1400, out_features=200, bias=True)\n",
            "    (2): PReLU(num_parameters=1)\n",
            "    (3): Dropout(p=0.0)\n",
            "    (4): Linear(in_features=200, out_features=1, bias=True)\n",
            "  )\n",
            "  (mol_atom_from_bond_ffn): Sequential(\n",
            "    (0): Dropout(p=0.0)\n",
            "    (1): Linear(in_features=1400, out_features=200, bias=True)\n",
            "    (2): PReLU(num_parameters=1)\n",
            "    (3): Dropout(p=0.0)\n",
            "    (4): Linear(in_features=200, out_features=1, bias=True)\n",
            "  )\n",
            "  (sigmoid): Sigmoid()\n",
            ")\n",
            "Number of parameters = 107,704,036\n",
            "Moving model to cuda\n",
            "Epoch: 0000 loss_train: 0.913277 loss_val: 0.516753 auc_val: 0.8389 cur_lr: 0.00058 t_time: 98.4495s v_time: 4.2515s\n",
            "Epoch: 0001 loss_train: 1.721792 loss_val: 0.533001 auc_val: 0.8704 cur_lr: 0.00099 t_time: 98.5393s v_time: 4.3243s\n",
            "Epoch: 0002 loss_train: 0.993730 loss_val: 0.521368 auc_val: 0.8727 cur_lr: 0.00074 t_time: 97.6698s v_time: 4.1529s\n",
            "Epoch: 0003 loss_train: 0.885105 loss_val: 0.512471 auc_val: 0.8579 cur_lr: 0.00055 t_time: 96.8057s v_time: 4.3926s\n",
            "Epoch: 0004 loss_train: 0.846696 loss_val: 0.516265 auc_val: 0.8575 cur_lr: 0.00041 t_time: 97.7059s v_time: 4.3478s\n",
            "Epoch: 0005 loss_train: 0.803921 loss_val: 0.506288 auc_val: 0.8689 cur_lr: 0.00031 t_time: 98.3722s v_time: 4.3406s\n",
            "Epoch: 0006 loss_train: 0.764083 loss_val: 0.505630 auc_val: 0.8730 cur_lr: 0.00023 t_time: 98.4826s v_time: 4.3059s\n",
            "Epoch: 0007 loss_train: 0.746934 loss_val: 0.499433 auc_val: 0.8789 cur_lr: 0.00017 t_time: 98.3984s v_time: 4.2735s\n",
            "Epoch: 0008 loss_train: 0.734157 loss_val: 0.501937 auc_val: 0.8723 cur_lr: 0.00013 t_time: 98.2836s v_time: 4.2241s\n",
            "Epoch: 0009 loss_train: 0.723555 loss_val: 0.500258 auc_val: 0.8725 cur_lr: 0.00010 t_time: 97.5619s v_time: 4.2902s\n",
            "Model 0 best val loss = 0.499433 on epoch 7\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.bias\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.output_linear.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_node.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_edge.weight\".\n",
            "Loading pretrained parameter \"readout.cached_zero_vector\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.bias\".\n",
            "Moving model to cuda\n",
            "Model 0 test auc = 0.855970\n",
            "Ensemble test auc = 0.855970\n",
            "3-fold cross validation\n",
            "Seed 0 ==> test auc = 0.892672\n",
            "Seed 1 ==> test auc = 0.902909\n",
            "Seed 2 ==> test auc = 0.855970\n",
            "overall_scaffold_balanced_test_auc=0.883850\n",
            "std=0.020152\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nE7eZZu4qxFl",
        "outputId": "f5fc05e2-3bc5-434a-c9d8-ee77ea56e5cf"
      },
      "source": [
        "!python grover/main.py predict --data_path grover/exampledata/finetune/bbbp.csv \\\n",
        "               --features_path grover/exampledata/finetune/bbbp.npz \\\n",
        "               --checkpoint_dir ./grover/model \\\n",
        "               --no_features_scaling \\\n",
        "               --output data_pre.csv"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[WARNING] Horovod cannot be imported; multi-GPU training is unsupported\n",
            "Loading training args\n",
            "Loading data\n",
            "Validating SMILES\n",
            "Test size = 2,039\n",
            "Predicting...\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
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            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_i.weight\".\n",
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            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.weight\".\n",
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            "Moving model to cuda\n",
            " 33% 1/3 [00:39<01:19, 39.61s/it]Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
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            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.bias\".\n",
            "Moving model to cuda\n",
            "100% 3/3 [01:56<00:00, 39.06s/it]\n",
            "Saving predictions to data_pre.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ee0fwCNB-PDP",
        "outputId": "9ff058b6-2389-46df-aae8-1abe78772816"
      },
      "source": [
        "!python grover/main.py eval --data_path grover/exampledata/finetune/bbbp.csv \\\n",
        "                    --features_path grover/exampledata/finetune/bbbp.npz \\\n",
        "                    --checkpoint_dir grover/model/finetune/bbbp \\\n",
        "                    --dataset_type classification \\\n",
        "                    --split_type scaffold_balanced \\\n",
        "                    --ensemble_size 1 \\\n",
        "                    --num_folds 3 \\\n",
        "                    --metric auc \\\n",
        "                    --no_features_scaling"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[WARNING] Horovod cannot be imported; multi-GPU training is unsupported\n",
            "Fold 0\n",
            "Loading data\n",
            "Number of tasks = 1\n",
            "Splitting data with seed 0\n",
            "100% 2039/2039 [00:00<00:00, 2371.32it/s]\n",
            "Total scaffolds = 1,025 | train scaffolds = 764 | val scaffolds = 123 | test scaffolds = 138\n",
            "Label averages per scaffold, in decreasing order of scaffold frequency,capped at 10 scaffolds and 20 labels: [(array([0.72992701]), array([137])), (array([1.]), array([1])), (array([0.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([0.]), array([1])), (array([1.]), array([1])), (array([1.]), array([2])), (array([0.]), array([2])), (array([1.]), array([1]))]\n",
            "Class sizes\n",
            "p_np 0: 23.49%, 1: 76.51%\n",
            "Total size = 2,039 | train size = 1,631 | val size = 203 | test size = 205\n",
            "Loading model 0 from grover/model/finetune/bbbp/fold_0/model_0/model.pt\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_node.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_edge.weight\".\n",
            "Loading pretrained parameter \"readout.cached_zero_vector\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.bias\".\n",
            "Moving model to cuda\n",
            "Number of parameters = 107,704,036\n",
            "Model test auc = 0.892672\n",
            "Fold 1\n",
            "Loading data\n",
            "Number of tasks = 1\n",
            "Splitting data with seed 1\n",
            "100% 2039/2039 [00:00<00:00, 2387.26it/s]\n",
            "Total scaffolds = 1,025 | train scaffolds = 768 | val scaffolds = 132 | test scaffolds = 125\n",
            "Label averages per scaffold, in decreasing order of scaffold frequency,capped at 10 scaffolds and 20 labels: [(array([0.72992701]), array([137])), (array([1.]), array([2])), (array([1.]), array([3])), (array([0.8]), array([5])), (array([1.]), array([9])), (array([1.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1]))]\n",
            "Class sizes\n",
            "p_np 0: 23.49%, 1: 76.51%\n",
            "Total size = 2,039 | train size = 1,631 | val size = 203 | test size = 205\n",
            "Loading model 1 from grover/model/finetune/bbbp/fold_1/model_0/model.pt\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_node.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_edge.weight\".\n",
            "Loading pretrained parameter \"readout.cached_zero_vector\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.bias\".\n",
            "Moving model to cuda\n",
            "Number of parameters = 107,704,036\n",
            "Model test auc = 0.902909\n",
            "Fold 2\n",
            "Loading data\n",
            "Number of tasks = 1\n",
            "Splitting data with seed 2\n",
            "100% 2039/2039 [00:00<00:00, 2345.24it/s]\n",
            "Total scaffolds = 1,025 | train scaffolds = 766 | val scaffolds = 125 | test scaffolds = 134\n",
            "Label averages per scaffold, in decreasing order of scaffold frequency,capped at 10 scaffolds and 20 labels: [(array([0.72992701]), array([137])), (array([1.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([0.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([1.]), array([1])), (array([0.]), array([5])), (array([1.]), array([1]))]\n",
            "Class sizes\n",
            "p_np 0: 23.49%, 1: 76.51%\n",
            "Total size = 2,039 | train size = 1,631 | val size = 203 | test size = 205\n",
            "Loading model 2 from grover/model/finetune/bbbp/fold_2/model_0/model.pt\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.edge_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.0.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.1.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.2.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_q.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_k.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.heads.3.mpn_v.W_h.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.layernorm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_i.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.0.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.linear_layers.2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.attn.output_linear.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.W_o.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.node_blocks.0.sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_atom_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_atom.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_1.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.W_2.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.ffn_bond_from_bond.act_func.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.atom_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_atom_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.bond_from_bond_sublayer.norm.bias\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_node.weight\".\n",
            "Loading pretrained parameter \"grover.encoders.act_func_edge.weight\".\n",
            "Loading pretrained parameter \"readout.cached_zero_vector\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_atom_ffn.4.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.1.bias\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.2.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.weight\".\n",
            "Loading pretrained parameter \"mol_atom_from_bond_ffn.4.bias\".\n",
            "Moving model to cuda\n",
            "Number of parameters = 107,704,036\n",
            "Model test auc = 0.855970\n",
            "3-fold cross validation\n",
            "Seed 0 ==> test auc = 0.892672\n",
            "Seed 1 ==> test auc = 0.902909\n",
            "Seed 2 ==> test auc = 0.855970\n",
            "overall_scaffold_balanced_test_auc=0.883850\n",
            "std=0.020152\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wG-HPw_h-X9L",
        "outputId": "bfeba5ee-8813-431a-b356-be3a20da2891"
      },
      "source": [
        "(0.892672+0.902909+0.855970)/3"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8838503333333333"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "URhpsmG_-nW2"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}