ImageNet-10_DPAC/notebook.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x7c-tSP9Wl0n",
        "outputId": "82be1465-f1af-4f87-ce64-4427e0290bdc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'Deep-Probability-Aggregation-Clustering'...\n",
            "remote: Enumerating objects: 62, done.\u001b[K\n",
            "remote: Counting objects: 100% (62/62), done.\u001b[K\n",
            "remote: Compressing objects: 100% (62/62), done.\u001b[K\n",
            "remote: Total 62 (delta 16), reused 0 (delta 0), pack-reused 0 (from 0)\u001b[K\n",
            "Receiving objects: 100% (62/62), 48.44 KiB | 826.00 KiB/s, done.\n",
            "Resolving deltas: 100% (16/16), done.\n",
            "/content/Deep-Probability-Aggregation-Clustering\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/aomandechenai/Deep-Probability-Aggregation-Clustering.git\n",
        "%cd Deep-Probability-Aggregation-Clustering"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n",
        "!chmod +x Miniconda3-latest-Linux-x86_64.sh\n",
        "!bash ./Miniconda3-latest-Linux-x86_64.sh -b -f -p /usr/local\n",
        "\n",
        "import sys\n",
        "sys.path.append('/usr/local/lib/python3.9/site-packages')\n",
        "\n",
        "!conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main\n",
        "!conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "QdE4lue_W90u",
        "outputId": "b4a866eb-8238-4085-b141-1a49f46b879a"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2025-08-06 17:09:30--  https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n",
            "Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.32.241, 104.16.191.158, 2606:4700::6810:20f1, ...\n",
            "Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.32.241|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 160039710 (153M) [application/octet-stream]\n",
            "Saving to: ‘Miniconda3-latest-Linux-x86_64.sh’\n",
            "\n",
            "Miniconda3-latest-L 100%[===================>] 152.62M   147MB/s    in 1.0s    \n",
            "\n",
            "2025-08-06 17:09:31 (147 MB/s) - ‘Miniconda3-latest-Linux-x86_64.sh’ saved [160039710/160039710]\n",
            "\n",
            "PREFIX=/usr/local\n",
            "Unpacking payload ...\n",
            "entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n",
            "entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n",
            "\n",
            "Installing base environment...\n",
            "\n",
            "Preparing transaction: ...working... done\n",
            "Executing transaction: ...working... done\n",
            "entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n",
            "installation finished.\n",
            "WARNING:\n",
            "    You currently have a PYTHONPATH environment variable set. This may cause\n",
            "    unexpected behavior when running the Python interpreter in Miniconda3.\n",
            "    For best results, please verify that your PYTHONPATH only points to\n",
            "    directories of packages that are compatible with the Python interpreter\n",
            "    in Miniconda3: /usr/local\n",
            "accepted Terms of Service for \u001b[4;94mhttps://repo.anaconda.com/pkgs/main\u001b[0m\n",
            "accepted Terms of Service for \u001b[4;94mhttps://repo.anaconda.com/pkgs/r\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!conda create -n newenv python=3.8 -y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "0HZNyXF2XDBU",
        "outputId": "4aace891-e3e9-45b7-eafe-c0b41792b45d"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1;32m2\u001b[0m\u001b[1;32m channel Terms of Service accepted\u001b[0m\n",
            "Channels:\n",
            " - defaults\n",
            "Platform: linux-64\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\bdone\n",
            "Solving environment: | \b\bdone\n",
            "\n",
            "\n",
            "==> WARNING: A newer version of conda exists. <==\n",
            "    current version: 25.5.1\n",
            "    latest version: 25.7.0\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/newenv\n",
            "\n",
            "  added / updated specs:\n",
            "    - python=3.8\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    ncurses-6.5                |       h7934f7d_0         1.1 MB\n",
            "    openssl-3.0.17             |       h5eee18b_0         5.2 MB\n",
            "    pip-24.2                   |   py38h06a4308_0         2.2 MB\n",
            "    python-3.8.20              |       he870216_0        23.8 MB\n",
            "    readline-8.3               |       hc2a1206_0         471 KB\n",
            "    setuptools-75.1.0          |   py38h06a4308_0         1.7 MB\n",
            "    wheel-0.44.0               |   py38h06a4308_0         108 KB\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:        34.5 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-5.1-1_gnu \n",
            "  ca-certificates    pkgs/main/linux-64::ca-certificates-2025.2.25-h06a4308_0 \n",
            "  ld_impl_linux-64   pkgs/main/linux-64::ld_impl_linux-64-2.40-h12ee557_0 \n",
            "  libffi             pkgs/main/linux-64::libffi-3.4.4-h6a678d5_1 \n",
            "  libgcc-ng          pkgs/main/linux-64::libgcc-ng-11.2.0-h1234567_1 \n",
            "  libgomp            pkgs/main/linux-64::libgomp-11.2.0-h1234567_1 \n",
            "  libstdcxx-ng       pkgs/main/linux-64::libstdcxx-ng-11.2.0-h1234567_1 \n",
            "  libxcb             pkgs/main/linux-64::libxcb-1.17.0-h9b100fa_0 \n",
            "  ncurses            pkgs/main/linux-64::ncurses-6.5-h7934f7d_0 \n",
            "  openssl            pkgs/main/linux-64::openssl-3.0.17-h5eee18b_0 \n",
            "  pip                pkgs/main/linux-64::pip-24.2-py38h06a4308_0 \n",
            "  pthread-stubs      pkgs/main/linux-64::pthread-stubs-0.3-h0ce48e5_1 \n",
            "  python             pkgs/main/linux-64::python-3.8.20-he870216_0 \n",
            "  readline           pkgs/main/linux-64::readline-8.3-hc2a1206_0 \n",
            "  setuptools         pkgs/main/linux-64::setuptools-75.1.0-py38h06a4308_0 \n",
            "  sqlite             pkgs/main/linux-64::sqlite-3.50.2-hb25bd0a_1 \n",
            "  tk                 pkgs/main/linux-64::tk-8.6.14-h993c535_1 \n",
            "  wheel              pkgs/main/linux-64::wheel-0.44.0-py38h06a4308_0 \n",
            "  xorg-libx11        pkgs/main/linux-64::xorg-libx11-1.8.12-h9b100fa_1 \n",
            "  xorg-libxau        pkgs/main/linux-64::xorg-libxau-1.0.12-h9b100fa_0 \n",
            "  xorg-libxdmcp      pkgs/main/linux-64::xorg-libxdmcp-1.1.5-h9b100fa_0 \n",
            "  xorg-xorgproto     pkgs/main/linux-64::xorg-xorgproto-2024.1-h5eee18b_1 \n",
            "  xz                 pkgs/main/linux-64::xz-5.6.4-h5eee18b_1 \n",
            "  zlib               pkgs/main/linux-64::zlib-1.2.13-h5eee18b_1 \n",
            "\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages:\n",
            "python-3.8.20        | 23.8 MB   | :   0% 0/1 [00:00<?, ?it/s]\n",
            "openssl-3.0.17       | 5.2 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\n",
            "\n",
            "pip-24.2             | 2.2 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "setuptools-75.1.0    | 1.7 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "ncurses-6.5          | 1.1 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "readline-8.3         | 471 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "wheel-0.44.0         | 108 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "python-3.8.20        | 23.8 MB   | :   0% 0.0006572008194954067/1 [00:00<02:56, 176.92s/it]\n",
            "\n",
            "\n",
            "setuptools-75.1.0    | 1.7 MB    | :   2% 0.01849850907707298/1 [00:00<00:06,  6.14s/it]\u001b[A\u001b[A\u001b[A\n",
            "openssl-3.0.17       | 5.2 MB    | :   0% 0.0029977792939885777/1 [00:00<00:41, 41.81s/it]\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "ncurses-6.5          | 1.1 MB    | :   1% 0.014401655346517857/1 [00:00<00:12, 12.33s/it]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "pip-24.2             | 2.2 MB    | : 100% 1.0/1 [00:00<00:00,  7.18s/it]                 \u001b[A\u001b[A\n",
            "\n",
            "\n",
            "python-3.8.20        | 23.8 MB   | :   8% 0.07689249588096257/1 [00:00<00:02,  2.37s/it]   \n",
            "openssl-3.0.17       | 5.2 MB    | :  32% 0.31776460516278926/1 [00:00<00:00,  1.69it/s]  \u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "readline-8.3         | 471 KB    | :   3% 0.03400397653924861/1 [00:00<00:06,  6.89s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "wheel-0.44.0         | 108 KB    | :  15% 0.14783134378186213/1 [00:00<00:01,  1.71s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "wheel-0.44.0         | 108 KB    | : 100% 1.0/1 [00:00<00:00,  1.71s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "readline-8.3         | 471 KB    | : 100% 1.0/1 [00:00<00:00,  6.89s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "ncurses-6.5          | 1.1 MB    | : 100% 1.0/1 [00:00<00:00,  4.35it/s]                 \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "python-3.8.20        | 23.8 MB   | :  25% 0.2477647089497683/1 [00:00<00:00,  1.01s/it] \n",
            "openssl-3.0.17       | 5.2 MB    | : 100% 1.0/1 [00:00<00:00,  3.05it/s]                \u001b[A\n",
            "python-3.8.20        | 23.8 MB   | : 100% 1.0/1 [00:01<00:00,  1.17s/it]\n",
            "\n",
            "\n",
            "setuptools-75.1.0    | 1.7 MB    | : 100% 1.0/1 [00:01<00:00,  1.12s/it]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "setuptools-75.1.0    | 1.7 MB    | : 100% 1.0/1 [00:01<00:00,  1.12s/it]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "pip-24.2             | 2.2 MB    | : 100% 1.0/1 [00:01<00:00,  1.13s/it]\u001b[A\u001b[A\n",
            "\n",
            "pip-24.2             | 2.2 MB    | : 100% 1.0/1 [00:01<00:00,  1.13s/it]\u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "wheel-0.44.0         | 108 KB    | : 100% 1.0/1 [00:01<00:00,  1.18s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "\n",
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            "wheel-0.44.0         | 108 KB    | : 100% 1.0/1 [00:01<00:00,  1.18s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "readline-8.3         | 471 KB    | : 100% 1.0/1 [00:01<00:00,  1.15s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "readline-8.3         | 471 KB    | : 100% 1.0/1 [00:01<00:00,  1.15s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "openssl-3.0.17       | 5.2 MB    | : 100% 1.0/1 [00:01<00:00,  3.05it/s]\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \n",
            "                                                                        \u001b[A\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\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\b\\ \b\bdone\n",
            "Executing transaction: / \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 newenv\n",
            "#\n",
            "# To deactivate an active environment, use\n",
            "#\n",
            "#     $ conda deactivate\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/Deep-Probability-Aggregation-Clustering/PAC_DPAC_program"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KtKYd48gXNB9",
        "outputId": "d8d1f444-f6ef-4242-b59b-d49b3bd764fd"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/Deep-Probability-Aggregation-Clustering/PAC_DPAC_program\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!source /usr/local/bin/activate newenv && pip install -r requirements.txt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "39cB532YXHAe",
        "outputId": "2960fa72-26e8-444f-d8c6-69ed7806d6ca"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting torch==1.7.1 (from -r requirements.txt (line 1))\n",
            "  Downloading torch-1.7.1-cp38-cp38-manylinux1_x86_64.whl.metadata (22 kB)\n",
            "Collecting torchvision==0.8.2 (from -r requirements.txt (line 2))\n",
            "  Downloading torchvision-0.8.2-cp38-cp38-manylinux1_x86_64.whl.metadata (7.2 kB)\n",
            "Collecting timm==0.4.12 (from -r requirements.txt (line 3))\n",
            "  Downloading timm-0.4.12-py3-none-any.whl.metadata (30 kB)\n",
            "Collecting Pillow (from -r requirements.txt (line 4))\n",
            "  Downloading pillow-10.4.0-cp38-cp38-manylinux_2_28_x86_64.whl.metadata (9.2 kB)\n",
            "Collecting blobfile (from -r requirements.txt (line 5))\n",
            "  Downloading blobfile-3.0.0-py3-none-any.whl.metadata (15 kB)\n",
            "Collecting mypy (from -r requirements.txt (line 6))\n",
            "  Downloading mypy-1.14.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl.metadata (2.1 kB)\n",
            "Collecting numpy (from -r requirements.txt (line 7))\n",
            "  Downloading numpy-1.24.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.6 kB)\n",
            "Collecting pytest (from -r requirements.txt (line 8))\n",
            "  Downloading pytest-8.3.5-py3-none-any.whl.metadata (7.6 kB)\n",
            "Collecting requests (from -r requirements.txt (line 9))\n",
            "  Downloading requests-2.32.4-py3-none-any.whl.metadata (4.9 kB)\n",
            "Collecting einops (from -r requirements.txt (line 10))\n",
            "  Downloading einops-0.8.1-py3-none-any.whl.metadata (13 kB)\n",
            "Collecting tensorboardX (from -r requirements.txt (line 11))\n",
            "  Downloading tensorboardX-2.6.2.2-py2.py3-none-any.whl.metadata (5.8 kB)\n",
            "Collecting scipy (from -r requirements.txt (line 13))\n",
            "  Downloading scipy-1.10.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (58 kB)\n",
            "Collecting typing-extensions (from torch==1.7.1->-r requirements.txt (line 1))\n",
            "  Downloading typing_extensions-4.13.2-py3-none-any.whl.metadata (3.0 kB)\n",
            "Collecting pycryptodomex>=3.8 (from blobfile->-r requirements.txt (line 5))\n",
            "  Downloading pycryptodomex-3.23.0-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.4 kB)\n",
            "Collecting urllib3<3,>=1.25.3 (from blobfile->-r requirements.txt (line 5))\n",
            "  Downloading urllib3-2.2.3-py3-none-any.whl.metadata (6.5 kB)\n",
            "Collecting lxml>=4.9 (from blobfile->-r requirements.txt (line 5))\n",
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            "Installing collected packages: urllib3, typing-extensions, tomli, pycryptodomex, protobuf, pluggy, Pillow, packaging, numpy, mypy-extensions, lxml, iniconfig, idna, filelock, einops, charset_normalizer, certifi, torch, tensorboardX, scipy, requests, mypy, exceptiongroup, blobfile, torchvision, pytest, timm\n",
            "Successfully installed Pillow-10.4.0 blobfile-3.0.0 certifi-2025.8.3 charset_normalizer-3.4.2 einops-0.8.1 exceptiongroup-1.3.0 filelock-3.16.1 idna-3.10 iniconfig-2.1.0 lxml-6.0.0 mypy-1.14.1 mypy-extensions-1.1.0 numpy-1.24.4 packaging-25.0 pluggy-1.5.0 protobuf-5.29.5 pycryptodomex-3.23.0 pytest-8.3.5 requests-2.32.4 scipy-1.10.1 tensorboardX-2.6.2.2 timm-0.4.12 tomli-2.2.1 torch-1.7.1 torchvision-0.8.2 typing-extensions-4.13.2 urllib3-2.2.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!source /usr/local/bin/activate newenv && pip install tqdm"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GqurpwL6Xpt_",
        "outputId": "01008aad-eefe-4b25-cea9-510caf09a9db"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting tqdm\n",
            "  Downloading tqdm-4.67.1-py3-none-any.whl.metadata (57 kB)\n",
            "Downloading tqdm-4.67.1-py3-none-any.whl (78 kB)\n",
            "Installing collected packages: tqdm\n",
            "Successfully installed tqdm-4.67.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#change line 80 of pretrain.py from\n",
        "#params_to_optimize = [{'params': model.resnet.parameters(), 'lr': 1e-4, 'weight_decay': 1e-4},\n",
        "#                          {'params': model.projection_head.parameters(), 'lr': 1e-4, 'weight_decay': 1e-4}]\n",
        "\n",
        "#to\n",
        "\n",
        "# params_to_optimize = [\n",
        "#     {'params': model.resnet.parameters(), 'lr': 1e-4, 'weight_decay': 1e-4},\n",
        "#     {'params': model.mlp.parameters(), 'lr': 1e-4, 'weight_decay': 1e-4}\n",
        "# ]\n",
        "\n"
      ],
      "metadata": {
        "id": "YjMnNtIOc1d_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!source /usr/local/bin/activate newenv && python pretrain_step.py"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gWQVmP6YXbVi",
        "outputId": "a3d23b0f-8925-407d-da95-48864ad1369d"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "select device:cuda0\n",
            "Files already downloaded and verified\n",
            "Files already downloaded and verified\n",
            "  0% 0/1000 [00:00<?, ?it/s]Epoch [0/1000]\tcontrastive_loss: 5.715244852066044\t \n",
            "  0% 1/1000 [03:07<51:54:43, 187.07s/it]\n",
            "Traceback (most recent call last):\n",
            "  File \"pretrain_step.py\", line 104, in <module>\n",
            "    main()\n",
            "  File \"pretrain_step.py\", line 97, in main\n",
            "    model, loss_epoch = train_model(args, scaler, ins_train_loader, optimizer, criterion, model)\n",
            "  File \"pretrain_step.py\", line 45, in train_model\n",
            "    for step, ((weak, strong, _), _) in enumerate(ins_train_loader):\n",
            "  File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py\", line 435, in __next__\n",
            "    data = self._next_data()\n",
            "  File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py\", line 1068, in _next_data\n",
            "    idx, data = self._get_data()\n",
            "  File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py\", line 1024, in _get_data\n",
            "  File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/utils/data/dataloader.py\", line 872, in _try_get_data\n",
            "    data = self._data_queue.get(timeout=timeout)\n",
            "  File \"/usr/local/envs/newenv/lib/python3.8/queue.py\", line 179, in get\n",
            "    self.not_empty.wait(remaining)\n",
            "  File \"/usr/local/envs/newenv/lib/python3.8/threading.py\", line 306, in wait\n",
            "    gotit = waiter.acquire(True, timeout)\n",
            "KeyboardInterrupt\n",
            "^C\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "2WP9OXJeaabz"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}