Delete Load_Example.ipynb

Load_Example.ipynb

@@ -1,63 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "import torch\n",
-    "from tqdm import tqdm\n",
-    "from load_i2e_datasets import I2E_Dataset\n",
-    "os.environ['HF_ENDPOINT'] = 'https://hf-mirror.com'            # Use HF mirror server in some regions"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "model_cache_path = 'Your path to model cache'\n",
-    "load_datasets = 'I2E-CIFAR10'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "train_dataset = I2E_Dataset(model_cache_path, load_datasets, split='train', transform=None, target_transform=None)\n",
-    "val_dataset = I2E_Dataset(model_cache_path, load_datasets, split='validation', transform=None, target_transform=None)\n",
-    "print(f\"Train samples: {len(train_dataset)}, Validation samples: {len(val_dataset)}\")\n",
-    "\n",
-    "# You can create dataloaders according to your needs\n",
-    "train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=256, shuffle=False, num_workers=32, pin_memory=False)\n",
-    "val_loader = torch.utils.data.DataLoader(val_dataset, batch_size=256, shuffle=False, num_workers=32, pin_memory=False)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "pytorch291n",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.14"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}