codeShare/lora-training-data
2785
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}1047 },1048 "cells": [1049 {1050 "cell_type": "code",1051 "execution_count": 22,1052 "metadata": {1053 "colab": {1054 "base_uri": "https://localhost:8080/",1055 "height": 309,1056 "referenced_widgets": [1057 "2e1f425b2f3e4d18a5036fe961804b39",1058 "d818e77ae09443f999eb6fc249255b93",1059 "858c08835bbc43d1b53c6fd091fdc52e",1060 "b9a3b84c1bc74fc28d4e83654b4f26e5",1061 "7002df0db93d41b39a2e27ceb6a7be58",1062 "36fcb14d4f45413094b1476c470767af",1063 "55c5120ed2794c72919269e06317b567",1064 "a43bc537526649fcad39b4adf96e620c",1065 "99256de0b03840c2a5072cf781b7f5ad",1066 "8b1fce564f334d38b978855fcfdba7f1",1067 "89aab0a940c04cad81dd77d373891892",1068 "74e77df1e60d4cd2bef03fc9e09f6781",1069 "9479d7198b934be8a2a0223b8518b3f7",1070 "4d1d03b651774493a57e92d2e6139638",1071 "1601e9e55e3040288dc729423d651537",1072 "2a69c33f21f945f1b25c543e39058ea0",1073 "4ffe3afdd90046f0b9fa91cc549797b0",1074 "bdbf3e3412fe401eb2442f02dd5d7ecc",1075 "80aaa28cfe4f47939ef5829e34e5513e",1076 "4ffe3f2b4839461ab08f43b911744b24",1077 "c4494ad824ab45639e047deb17477120",1078 "91f1eb8615d24c359788a4ed9f9b899e"1079 ]1080 },1081 "id": "9ul9xNLYEzTj",1082 "outputId": "e727ac39-cd53-435b-f7bf-094284282c45"1083 },1084 "outputs": [1085 {1086 "output_type": "stream",1087 "name": "stdout",1088 "text": [1089 "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n",1090 "✅ torchao updated to version: 0.17.0\n",1091 "✅ Dependencies installed\n",1092 "✅ Logged into Hugging Face\n",1093 " [GPU 0] Loading...\n"1094 ]1095 },1096 {1097 "output_type": "display_data",1098 "data": {1099 "text/plain": [1100 "Loading pipeline components...: 0%| | 0/5 [00:00<?, ?it/s]"1101 ],1102 "application/vnd.jupyter.widget-view+json": {1103 "version_major": 2,1104 "version_minor": 0,1105 "model_id": "2e1f425b2f3e4d18a5036fe961804b39"1106 }1107 },1108 "metadata": {}1109 },1110 {1111 "output_type": "display_data",1112 "data": {1113 "text/plain": [1114 "Loading weights: 0%| | 0/902 [00:00<?, ?it/s]"1115 ],1116 "application/vnd.jupyter.widget-view+json": {1117 "version_major": 2,1118 "version_minor": 0,1119 "model_id": "74e77df1e60d4cd2bef03fc9e09f6781"1120 }1121 },1122 "metadata": {}1123 },1124 {1125 "output_type": "stream",1126 "name": "stderr",1127 "text": [1128 "The config attributes {'decoder_block_out_channels': None} were passed to AutoencoderKLFlux2, but are not expected and will be ignored. Please verify your config.json configuration file.\n"1129 ]1130 },1131 {1132 "output_type": "stream",1133 "name": "stdout",1134 "text": [1135 " [GPU 0] Ready | VRAM: 12.40 GB\n",1136 "loaded pipe to cuda:0\n",1137 "trainable params: 16,711,680 || all params: 2,167,021,056 || trainable%: 0.7712\n",1138 "Converting transformer for training (bfloat16)...\n",1139 "Trainable parameters: 3,697,213,440\n",1140 "trainable params: 3,697,213,440 || all params: 3,892,256,256 || trainable%: 94.9890\n"1141 ]1142 }1143 ],1144 "source": [1145 "#@markdown # CELL 1 — Setup environment + login\n",1146 "from google.colab import drive, userdata\n",1147 "from huggingface_hub import login\n",1148 "import torch, os, gc\n",1149 "drive.mount(\"/content/drive\")\n",1150 "hf_token = userdata.get(\"HF_TOKEN\")\n",1151 "if hf_token:\n",1152 " login(token=hf_token)\n",1153 "else:\n",1154 " raise ValueError(\"HF_TOKEN not found in Google Colab secrets\")\n",1155 "#----#\n",1156 "\n",1157 "!pip uninstall -q torchao -y\n",1158 "!pip install -q torchao==0.17.0 --no-deps\n",1159 "\n",1160 "import torchao\n",1161 "print(f\"✅ torchao updated to version: {torchao.__version__}\")\n",1162 "!pip install -q safetensors huggingface_hub diffusers transformers accelerate sdnq\n",1163 "\n",1164 "#images for testing\n",1165 "# Resize so longest side is no greater than 1024px prior to\n",1166 "#prior to encoding into VAE\n",1167 "image1_path = '/content/drive/MyDrive/image1.jpg'\n",1168 "image2_path = '/content/drive/MyDrive/image2.jpg'\n",1169 "\n",1170 "# Test prompts\n",1171 "prompt1= 'a cute dog on grass'\n",1172 "prompt2 = 'a golden retriever on a road'\n",1173 "#-----#\n",1174 "print(\"✅ Dependencies installed\")\n",1175 "print(\"✅ Logged into Hugging Face\")\n",1176 "\n",1177 "import gc\n",1178 "import torch\n",1179 "from diffusers import Flux2KleinPipeline\n",1180 "#----#\n",1181 "from sdnq import SDNQConfig\n",1182 "from sdnq.common import use_torch_compile as triton_is_available\n",1183 "from sdnq.training import convert_sdnq_model_to_training\n",1184 "from sdnq.training import sdnq_training_post_load_quant\n",1185 "from sdnq.loader import apply_sdnq_options_to_model\n",1186 "#----#\n",1187 "from functools import partial\n",1188 "from safetensors.torch import load_file, save_file\n",1189 "from huggingface_hub import hf_hub_download\n",1190 "import hashlib\n",1191 "from pathlib import Path\n",1192 "import torch\n",1193 "from transformers import BitsAndBytesConfig\n",1194 "\n",1195 "# Patch function\n",1196 "def patch_encode_prompt(pipe, cached_prompt_embeds, cached_text_ids, gpu_id):\n",1197 " def patched(self, prompt=None, device=None, num_images_per_prompt=1, prompt_embeds=None, **kwargs):\n",1198 " device = device or torch.device(f\"cuda:{gpu_id}\")\n",1199 " if prompt_embeds is None:\n",1200 " emb = cached_prompt_embeds.to(device)\n",