16.1 kB

	{
	"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",
	"execution_count": 1,
	"metadata": {
	"id": "cCdVZlzUhePK",
	"outputId": "da3ed304-6143-4e22-c7fa-24ea16736064",
	"colab": {
	"base_uri": "https://localhost:8080/"
	}
	},
	"outputs": [
	{
	"output_type": "stream",
	"name": "stdout",
	"text": [
	"Cloning into 'FSGDM'...\n",
	"remote: Enumerating objects: 55, done.\u001b[K\n",
	"remote: Counting objects: 100% (55/55), done.\u001b[K\n",
	"remote: Compressing objects: 100% (45/45), done.\u001b[K\n",
	"remote: Total 55 (delta 20), reused 25 (delta 7), pack-reused 0 (from 0)\u001b[K\n",
	"Receiving objects: 100% (55/55), 22.79 KiB \| 11.39 MiB/s, done.\n",
	"Resolving deltas: 100% (20/20), done.\n"
	]
	}
	],
	"source": [
	"!git clone https://github.com/yinleung/FSGDM.git"
	]
	},
	{
	"cell_type": "code",
	"source": [
	"%cd FSGDM"
	],
	"metadata": {
	"id": "4OhZbKcyhkgl",
	"colab": {
	"base_uri": "https://localhost:8080/"
	},
	"outputId": "a626a392-ebb5-474c-c2e4-695b684abd3a"
	},
	"execution_count": 2,
	"outputs": [
	{
	"output_type": "stream",
	"name": "stdout",
	"text": [
	"/content/FSGDM\n"
	]
	}
	]
	},
	{
	"cell_type": "code",
	"source": [
	"!pip install fsgdm"
	],
	"metadata": {
	"colab": {
	"base_uri": "https://localhost:8080/"
	},
	"id": "tQzPOzUYxMtl",
	"outputId": "58da7294-dd66-4e8f-eeb4-c443398b96f5"
	},
	"execution_count": 3,
	"outputs": [
	{
	"output_type": "stream",
	"name": "stdout",
	"text": [
	"Collecting fsgdm\n",
	" Downloading fsgdm-1.0-py3-none-any.whl.metadata (4.2 kB)\n",
	"Requirement already satisfied: torch>=1.7.0 in /usr/local/lib/python3.11/dist-packages (from fsgdm) (2.6.0+cu124)\n",
	"Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from torch>=1.7.0->fsgdm) (3.18.0)\n",
	"Requirement already satisfied: typing-extensions>=4.10.0 in /usr/local/lib/python3.11/dist-packages (from torch>=1.7.0->fsgdm) (4.14.1)\n",
	"Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch>=1.7.0->fsgdm) (3.5)\n",
	"Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch>=1.7.0->fsgdm) (3.1.6)\n",
	"Requirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages (from torch>=1.7.0->fsgdm) (2025.3.0)\n",
	"Collecting nvidia-cuda-nvrtc-cu12==12.4.127 (from torch>=1.7.0->fsgdm)\n",
	" Downloading nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
	"Collecting nvidia-cuda-runtime-cu12==12.4.127 (from torch>=1.7.0->fsgdm)\n",
	" Downloading nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
	"Collecting nvidia-cuda-cupti-cu12==12.4.127 (from torch>=1.7.0->fsgdm)\n",
	" Downloading nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
	"Collecting nvidia-cudnn-cu12==9.1.0.70 (from torch>=1.7.0->fsgdm)\n",
	" Downloading nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
	"Collecting nvidia-cublas-cu12==12.4.5.8 (from torch>=1.7.0->fsgdm)\n",
	" Downloading nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
	"Collecting nvidia-cufft-cu12==11.2.1.3 (from torch>=1.7.0->fsgdm)\n",
	" Downloading nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
	"Collecting nvidia-curand-cu12==10.3.5.147 (from torch>=1.7.0->fsgdm)\n",
	" Downloading nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
	"Collecting nvidia-cusolver-cu12==11.6.1.9 (from torch>=1.7.0->fsgdm)\n",
	" Downloading nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
	"Collecting nvidia-cusparse-cu12==12.3.1.170 (from torch>=1.7.0->fsgdm)\n",
	" Downloading nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\n",
	"Requirement already satisfied: nvidia-cusparselt-cu12==0.6.2 in /usr/local/lib/python3.11/dist-packages (from torch>=1.7.0->fsgdm) (0.6.2)\n",
	"Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch>=1.7.0->fsgdm) (2.21.5)\n",
	"Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.7.0->fsgdm) (12.4.127)\n",
	"Collecting nvidia-nvjitlink-cu12==12.4.127 (from torch>=1.7.0->fsgdm)\n",
	" Downloading nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\n",
	"Requirement already satisfied: triton==3.2.0 in /usr/local/lib/python3.11/dist-packages (from torch>=1.7.0->fsgdm) (3.2.0)\n",
	"Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/dist-packages (from torch>=1.7.0->fsgdm) (1.13.1)\n",
	"Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch>=1.7.0->fsgdm) (1.3.0)\n",
	"Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch>=1.7.0->fsgdm) (3.0.2)\n",
	"Downloading fsgdm-1.0-py3-none-any.whl (8.9 kB)\n",
	"Downloading nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl (363.4 MB)\n",
	"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m363.4/363.4 MB\u001b[0m \u001b[31m3.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
	"\u001b[?25hDownloading nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (13.8 MB)\n",
	"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.8/13.8 MB\u001b[0m \u001b[31m63.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
	"\u001b[?25hDownloading nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (24.6 MB)\n",
	"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.6/24.6 MB\u001b[0m \u001b[31m37.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
	"\u001b[?25hDownloading nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (883 kB)\n",
	"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m883.7/883.7 kB\u001b[0m \u001b[31m54.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
	"\u001b[?25hDownloading nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl (664.8 MB)\n",
	"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m664.8/664.8 MB\u001b[0m \u001b[31m1.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
	"\u001b[?25hDownloading nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl (211.5 MB)\n",
	"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.5/211.5 MB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
	"\u001b[?25hDownloading nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl (56.3 MB)\n",
	"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.3/56.3 MB\u001b[0m \u001b[31m11.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
	"\u001b[?25hDownloading nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl (127.9 MB)\n",
	"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m127.9/127.9 MB\u001b[0m \u001b[31m7.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
	"\u001b[?25hDownloading nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl (207.5 MB)\n",
	"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.5/207.5 MB\u001b[0m \u001b[31m5.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
	"\u001b[?25hDownloading nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (21.1 MB)\n",
	"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m104.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
	"\u001b[?25hInstalling collected packages: nvidia-nvjitlink-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, fsgdm\n",
	" Attempting uninstall: nvidia-nvjitlink-cu12\n",
	" Found existing installation: nvidia-nvjitlink-cu12 12.5.82\n",
	" Uninstalling nvidia-nvjitlink-cu12-12.5.82:\n",
	" Successfully uninstalled nvidia-nvjitlink-cu12-12.5.82\n",
	" Attempting uninstall: nvidia-curand-cu12\n",
	" Found existing installation: nvidia-curand-cu12 10.3.6.82\n",
	" Uninstalling nvidia-curand-cu12-10.3.6.82:\n",
	" Successfully uninstalled nvidia-curand-cu12-10.3.6.82\n",
	" Attempting uninstall: nvidia-cufft-cu12\n",
	" Found existing installation: nvidia-cufft-cu12 11.2.3.61\n",
	" Uninstalling nvidia-cufft-cu12-11.2.3.61:\n",
	" Successfully uninstalled nvidia-cufft-cu12-11.2.3.61\n",
	" Attempting uninstall: nvidia-cuda-runtime-cu12\n",
	" Found existing installation: nvidia-cuda-runtime-cu12 12.5.82\n",
	" Uninstalling nvidia-cuda-runtime-cu12-12.5.82:\n",
	" Successfully uninstalled nvidia-cuda-runtime-cu12-12.5.82\n",
	" Attempting uninstall: nvidia-cuda-nvrtc-cu12\n",
	" Found existing installation: nvidia-cuda-nvrtc-cu12 12.5.82\n",
	" Uninstalling nvidia-cuda-nvrtc-cu12-12.5.82:\n",
	" Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.5.82\n",
	" Attempting uninstall: nvidia-cuda-cupti-cu12\n",
	" Found existing installation: nvidia-cuda-cupti-cu12 12.5.82\n",
	" Uninstalling nvidia-cuda-cupti-cu12-12.5.82:\n",
	" Successfully uninstalled nvidia-cuda-cupti-cu12-12.5.82\n",
	" Attempting uninstall: nvidia-cublas-cu12\n",
	" Found existing installation: nvidia-cublas-cu12 12.5.3.2\n",
	" Uninstalling nvidia-cublas-cu12-12.5.3.2:\n",
	" Successfully uninstalled nvidia-cublas-cu12-12.5.3.2\n",
	" Attempting uninstall: nvidia-cusparse-cu12\n",
	" Found existing installation: nvidia-cusparse-cu12 12.5.1.3\n",
	" Uninstalling nvidia-cusparse-cu12-12.5.1.3:\n",
	" Successfully uninstalled nvidia-cusparse-cu12-12.5.1.3\n",
	" Attempting uninstall: nvidia-cudnn-cu12\n",
	" Found existing installation: nvidia-cudnn-cu12 9.3.0.75\n",
	" Uninstalling nvidia-cudnn-cu12-9.3.0.75:\n",
	" Successfully uninstalled nvidia-cudnn-cu12-9.3.0.75\n",
	" Attempting uninstall: nvidia-cusolver-cu12\n",
	" Found existing installation: nvidia-cusolver-cu12 11.6.3.83\n",
	" Uninstalling nvidia-cusolver-cu12-11.6.3.83:\n",
	" Successfully uninstalled nvidia-cusolver-cu12-11.6.3.83\n",
	"Successfully installed fsgdm-1.0 nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nvjitlink-cu12-12.4.127\n"
	]
	}
	]
	},
	{
	"cell_type": "code",
	"source": [
	"%cd examples/CIFAR100/"
	],
	"metadata": {
	"colab": {
	"base_uri": "https://localhost:8080/"
	},
	"id": "nis69XVJxpSO",
	"outputId": "dc1f0bb5-9bd5-46ce-c1ef-722e699434d3"
	},
	"execution_count": 4,
	"outputs": [
	{
	"output_type": "stream",
	"name": "stdout",
	"text": [
	"/content/FSGDM/examples/CIFAR100\n"
	]
	}
	]
	},
	{
	"cell_type": "code",
	"source": [
	"!python main.py"
	],
	"metadata": {
	"colab": {
	"base_uri": "https://localhost:8080/"
	},
	"id": "PYsENziixteU",
	"outputId": "26e697b2-e04f-42dc-96fc-e9ca31a05d05"
	},
	"execution_count": 5,
	"outputs": [
	{
	"output_type": "stream",
	"name": "stdout",
	"text": [
	"Using device: cuda\n",
	"100% 169M/169M [00:05<00:00, 30.8MB/s]\n",
	"/usr/local/lib/python3.11/dist-packages/torch/utils/data/dataloader.py:624: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n",
	" warnings.warn(\n",
	"Epoch 1/300\n",
	"Test set: Average loss: 4.1882, Accuracy: 738/10000 (7.38%)\n",
	"Epoch 2/300\n",
	"Traceback (most recent call last):\n",
	" File \"/content/FSGDM/examples/CIFAR100/main.py\", line 208, in <module>\n",
	" main(args)\n",
	" File \"/content/FSGDM/examples/CIFAR100/main.py\", line 161, in main\n",
	" train_loss, train_acc = train_one_epoch(model, train_loader, criterion, optimizer, device)\n",
	" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
	" File \"/content/FSGDM/examples/CIFAR100/main.py\", line 102, in train_one_epoch\n",
	" running_loss += loss.item() * inputs.size(0)\n",
	" ^^^^^^^^^^^\n",
	"KeyboardInterrupt\n"
	]
	}
	]
	},
	{
	"cell_type": "code",
	"source": [],
	"metadata": {
	"id": "05BwserLxwTm"
	},
	"execution_count": null,
	"outputs": []
	}
	]
	}

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