Fashion-MNIST_GECCO/notebook.ipynb

{
  "nbformat": 4,
  "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",
      "source": [
        "#change  train.py\n",
        "#line 6 : from util import new_model, load_model, load_checkpoint, load_fashion_mnist\n",
        "#line 18 : device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
        "#line 20 : trainloader, testloader = load_fashion_mnist()\n",
        "\n",
        "#change model.py\n",
        "#line 13 : device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")"
      ],
      "metadata": {
        "id": "E0_TrZ4bwwR2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S0PIt1ZSuflC",
        "outputId": "7eec21f3-9767-4923-d170-a79100858198"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'GECCO'...\n",
            "remote: Enumerating objects: 77, done.\u001b[K\n",
            "remote: Counting objects: 100% (77/77), done.\u001b[K\n",
            "remote: Compressing objects: 100% (75/75), done.\u001b[K\n",
            "remote: Total 77 (delta 46), reused 4 (delta 2), pack-reused 0 (from 0)\u001b[K\n",
            "Receiving objects: 100% (77/77), 26.04 KiB | 5.21 MiB/s, done.\n",
            "Resolving deltas: 100% (46/46), done.\n",
            "/content/GECCO\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/GECCOProject/GECCO.git\n",
        "%cd GECCO"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "print(torch.__version__)\n",
        "print(torch.version.cuda)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fR7ljq1DvqmU",
        "outputId": "2c416c4d-db68-4145-8dc9-69af9b164258"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2.6.0+cu124\n",
            "12.4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install torch-geometric\n",
        "!pip install torch-scatter torch-sparse torch-cluster torch-spline-conv \\\n",
        "  -f https://data.pyg.org/whl/torch-2.6.0+cu124.html   #https://data.pyg.org/whl/torch-${TORCH}+${CUDA}.html"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2JlfZ3Rjvt_j",
        "outputId": "93adb6fb-39eb-410a-9df8-b26b0c86789b"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting torch-geometric\n",
            "  Downloading torch_geometric-2.6.1-py3-none-any.whl.metadata (63 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/63.1 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m63.1/63.1 kB\u001b[0m \u001b[31m3.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: aiohttp in /usr/local/lib/python3.11/dist-packages (from torch-geometric) (3.12.15)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages (from torch-geometric) (2025.3.0)\n",
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            "Requirement already satisfied: numpy in /usr/local/lib/python3.11/dist-packages (from torch-geometric) (2.0.2)\n",
            "Requirement already satisfied: psutil>=5.8.0 in /usr/local/lib/python3.11/dist-packages (from torch-geometric) (5.9.5)\n",
            "Requirement already satisfied: pyparsing in /usr/local/lib/python3.11/dist-packages (from torch-geometric) (3.2.3)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from torch-geometric) (2.32.3)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages (from torch-geometric) (4.67.1)\n",
            "Requirement already satisfied: aiohappyeyeballs>=2.5.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->torch-geometric) (2.6.1)\n",
            "Requirement already satisfied: aiosignal>=1.4.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->torch-geometric) (1.4.0)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->torch-geometric) (25.3.0)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.11/dist-packages (from aiohttp->torch-geometric) (1.7.0)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.11/dist-packages (from aiohttp->torch-geometric) (6.6.4)\n",
            "Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->torch-geometric) (0.3.2)\n",
            "Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->torch-geometric) (1.20.1)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch-geometric) (3.0.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->torch-geometric) (3.4.3)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests->torch-geometric) (3.10)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests->torch-geometric) (2.5.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests->torch-geometric) (2025.8.3)\n",
            "Requirement already satisfied: typing-extensions>=4.2 in /usr/local/lib/python3.11/dist-packages (from aiosignal>=1.4.0->aiohttp->torch-geometric) (4.14.1)\n",
            "Downloading torch_geometric-2.6.1-py3-none-any.whl (1.1 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m58.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: torch-geometric\n",
            "Successfully installed torch-geometric-2.6.1\n",
            "Looking in links: https://data.pyg.org/whl/torch-2.6.0+cu124.html\n",
            "Collecting torch-scatter\n",
            "  Downloading https://data.pyg.org/whl/torch-2.6.0%2Bcu124/torch_scatter-2.1.2%2Bpt26cu124-cp311-cp311-linux_x86_64.whl (10.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.8/10.8 MB\u001b[0m \u001b[31m127.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting torch-sparse\n",
            "  Downloading https://data.pyg.org/whl/torch-2.6.0%2Bcu124/torch_sparse-0.6.18%2Bpt26cu124-cp311-cp311-linux_x86_64.whl (5.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.0/5.0 MB\u001b[0m \u001b[31m65.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting torch-cluster\n",
            "  Downloading https://data.pyg.org/whl/torch-2.6.0%2Bcu124/torch_cluster-1.6.3%2Bpt26cu124-cp311-cp311-linux_x86_64.whl (3.4 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.4/3.4 MB\u001b[0m \u001b[31m107.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting torch-spline-conv\n",
            "  Downloading https://data.pyg.org/whl/torch-2.6.0%2Bcu124/torch_spline_conv-1.2.2%2Bpt26cu124-cp311-cp311-linux_x86_64.whl (1.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m61.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: scipy in /usr/local/lib/python3.11/dist-packages (from torch-sparse) (1.16.1)\n",
            "Requirement already satisfied: numpy<2.6,>=1.25.2 in /usr/local/lib/python3.11/dist-packages (from scipy->torch-sparse) (2.0.2)\n",
            "Installing collected packages: torch-spline-conv, torch-scatter, torch-sparse, torch-cluster\n",
            "Successfully installed torch-cluster-1.6.3+pt26cu124 torch-scatter-2.1.2+pt26cu124 torch-sparse-0.6.18+pt26cu124 torch-spline-conv-1.2.2+pt26cu124\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%mkdir models"
      ],
      "metadata": {
        "id": "9O5LeSEBzTZG"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!python train.py"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cVdHLBorvgTz",
        "outputId": "7f7cb394-3504-4f49-bf4b-6111e2e16a5c"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Create new model\n",
            "  0% 0/1875 [00:00<?, ?it/s]\n",
            "  0% 0/1875 [00:00<?, ?it/s]           \n",
            "  0% 0/1875 [00:00<?, ?it/s]           \n",
            "  0% 0/1875 [00:00<?, ?it/s]            \n",
            "  0% 0/1875 [00:00<?, ?it/s]           \n",
            "  0% 0/1875 [00:00<?, ?it/s]           \n",
            "  0% 0/1875 [00:00<?, ?it/s]           \n",
            " 87% 1623/1875 [00:16<00:02, 94.84it/s]Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x10774c434e00>\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.11/dist-packages/torch/utils/data/dataloader.py\", line 1618, in __del__\n",
            "    self._shutdown_workers()\n",
            "  File \"/usr/local/lib/python3.11/dist-packages/torch/utils/data/dataloader.py\", line 1582, in _shutdown_workers\n",
            "    w.join(timeout=_utils.MP_STATUS_CHECK_INTERVAL)\n",
            "  File \"/usr/lib/python3.11/multiprocessing/process.py\", line 149, in join\n",
            "    res = self._popen.wait(timeout)\n",
            "          ^^^^^^^^^^^^^^^^^^^^^^^^^\n",
            "  File \"/usr/lib/python3.11/multiprocessing/popen_fork.py\", line 40, in wait\n",
            "    if not wait([self.sentinel], timeout):\n",
            "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
            "  File \"/usr/lib/python3.11/multiprocessing/connection.py\", line 948, in wait\n",
            "    ready = selector.select(timeout)\n",
            "            ^^^^^^^^^^^^^^^^^^^^^^^^\n",
            "  File \"/usr/lib/python3.11/selectors.py\", line 415, in select\n",
            "    fd_event_list = self._selector.poll(timeout)\n",
            "                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
            "KeyboardInterrupt: \n",
            "  1% 6/1000 [02:21<6:30:09, 23.55s/it]\n",
            "Traceback (most recent call last):\n",
            "  File \"/content/GECCO/train.py\", line 60, in <module>\n",
            "    loss.backward()\n",
            "  File \"/usr/local/lib/python3.11/dist-packages/torch/_tensor.py\", line 626, in backward\n",
            "    torch.autograd.backward(\n",
            "  File \"/usr/local/lib/python3.11/dist-packages/torch/autograd/__init__.py\", line 339, in backward\n",
            "    grad_tensors_ = _tensor_or_tensors_to_tuple(grad_tensors, len(tensors))\n",
            "                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
            "  File \"/usr/local/lib/python3.11/dist-packages/torch/autograd/__init__.py\", line 232, in _tensor_or_tensors_to_tuple\n",
            "    def _tensor_or_tensors_to_tuple(\n",
            "    \n",
            "KeyboardInterrupt\n",
            " 87% 1627/1875 [00:17<00:02, 94.30it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "VTtcyldkvidn"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}