Upload cifar10_example.ipynb

cifar10_example.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "private_outputs": true,
+      "provenance": [],
+      "gpuType": "T4"
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "accelerator": "GPU"
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "eUREgErj2o-Z"
+      },
+      "outputs": [],
+      "source": [
+        "!git clone https://github.com/Won-Seong/simple-latent-diffusion-model.git\n",
+        "\n",
+        "import os\n",
+        "os.chdir('simple-latent-diffusion-model')  # Replace with your repository name\n",
+        "os.chdir('simple-latent-diffusion-model')  # Replace with your repository name\n",
+        "\n",
+        "from google.colab import drive\n",
+        "drive.mount('/content/drive')\n",
+        "\n",
+        "from diffusion_model.models.diffusion_model import DiffusionModel\n",
+        "from diffusion_model.sampler.ddim import DDIM\n",
+        "from diffusion_model.sampler.ddpm import DDPM\n",
+        "from diffusion_model.network.unet import Unet\n",
+        "from diffusion_model.network.unet_wrapper import UnetWrapper\n",
+        "from helper.painter import Painter\n",
+        "from helper.trainer import Trainer\n",
+        "from helper.data_generator import DataGenerator\n",
+        "from helper.loader import Loader\n",
+        "from helper.cond_encoder import ConditionEncoder\n",
+        "import torch"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "IMAGE_SHAPE = (3, 32, 32)\n",
+        "#CONFIG_PATH = 'Config Path'\n",
+        "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu'); device"
+      ],
+      "metadata": {
+        "id": "iN360_ddTmUr"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "sampler = DDIM(CONFIG_PATH)\n",
+        "cond_encoder = ConditionEncoder(CONFIG_PATH)\n",
+        "network = UnetWrapper(Unet, CONFIG_PATH, cond_encoder)\n",
+        "dm = DiffusionModel(network, sampler, IMAGE_SHAPE)\n",
+        "painter = Painter()\n",
+        "data_generator = DataGenerator()\n",
+        "loader = Loader()"
+      ],
+      "metadata": {
+        "id": "RK7nLUEDTzit"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "dm = loader.model_load('cifar10_diffusion', dm, is_ema=True) # Modify the model path"
+      ],
+      "metadata": {
+        "id": "lNCz3WUOWezr"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Inference\n",
+        "dm.eval()\n",
+        "sample = dm(9, y = 0)"
+      ],
+      "metadata": {
+        "id": "3bAjCEDbWn3p"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "painter.show_images(sample)"
+      ],
+      "metadata": {
+        "id": "ixVSSEhwikrv"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}