{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b01332d1-1384-4405-8af6-335c768da6e2",
   "metadata": {},
   "source": [
    "## SDXL LoRA Trainer by TheLastBen https://github.com/TheLastBen/fast-stable-diffusion, if you encounter any issues, feel free to discuss them."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f82bb3b-76de-4e2c-9251-df918f8f2cbe",
   "metadata": {},
   "source": [
    "# Dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3d144e06-1f7a-467b-9cf1-452bf773f0ab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d1e84d74d92c46f8aa78c03f50a0d0d8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Button(button_style='success', description='Done!', disabled=True, icon='check', style=ButtonStyle(), tooltip=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Install the dependencies\n",
    "\n",
    "force_reinstall= False\n",
    "\n",
    "# Set to true only if you want to install the dependencies again.\n",
    "\n",
    "#--------------------\n",
    "with open('/dev/null', 'w') as devnull:import requests, os, time, importlib;open('/workspace/sdxllorarunpod.py', 'wb').write(requests.get('https://huggingface.co/datasets/TheLastBen/RNPD/raw/main/Scripts/sdxllorarunpod.py').content);os.chdir('/workspace');import sdxllorarunpod;importlib.reload(sdxllorarunpod);from sdxllorarunpod import *;restored=False;restoreda=False;Deps(force_reinstall)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "461b7686-e4aa-4fa8-ab6f-5a6acbf4c601",
   "metadata": {},
   "source": [
    "# Download the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2f705bd1-35c9-49bd-84fd-03a1348cbe83",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;32mUsing SDXL model\n"
     ]
    }
   ],
   "source": [
    "# Run the cell to download the model\n",
    "\n",
    "#-------------\n",
    "MODEL_NAMExl=dls_xlf(\"\", \"\", \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e22327b-e0c3-424c-82e1-fb7f8a815c0b",
   "metadata": {},
   "source": [
    "# Create/Load a Session"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ac69c221-205a-40d2-b42e-6c8d515a43cc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;32mCreating session...\n",
      "\u001b[1;32mSession created, proceed to uploading instance images\n"
     ]
    }
   ],
   "source": [
    "Session_Name = \"aether_skin_230808_SDXL_LoRA_128_dim_50_epochs\"\n",
    "\n",
    "# Enter the session name, it if it exists, it will load it, otherwise it'll create an new session.\n",
    "\n",
    "#-----------------\n",
    "[WORKSPACE, Session_Name, INSTANCE_NAME, OUTPUT_DIR, SESSION_DIR, INSTANCE_DIR, CAPTIONS_DIR, MDLPTH, MODEL_NAMExl]=sess_xl(Session_Name, MODEL_NAMExl if 'MODEL_NAMExl' in locals() else \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d239e77-f7fd-404b-8006-081f15326412",
   "metadata": {},
   "source": [
    "# Train LoRA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c54a7335-8402-42f2-9a71-9da99f6ea604",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34m'########:'########:::::'###::::'####:'##::: ##:'####:'##::: ##::'######:::\n",
      "... ##..:: ##.... ##:::'## ##:::. ##:: ###:: ##:. ##:: ###:: ##:'##... ##::\n",
      "::: ##:::: ##:::: ##::'##:. ##::: ##:: ####: ##:: ##:: ####: ##: ##:::..:::\n",
      "::: ##:::: ########::'##:::. ##:: ##:: ## ## ##:: ##:: ## ## ##: ##::'####:\n",
      "::: ##:::: ##.. ##::: #########:: ##:: ##. ####:: ##:: ##. ####: ##::: ##::\n",
      "::: ##:::: ##::. ##:: ##.... ##:: ##:: ##:. ###:: ##:: ##:. ###: ##::: ##::\n",
      "::: ##:::: ##:::. ##: ##:::: ##:'####: ##::. ##:'####: ##::. ##:. ######:::\n",
      ":::..:::::..:::::..::..:::::..::....::..::::..::....::..::::..:::......::::\n",
      "\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Progress:  71%|███████   | 676/950 [06:22<02:23,  1.91it/s, loss=0.245, lr=5.75e-7]  "
     ]
    }
   ],
   "source": [
    "Resume_Training= False\n",
    "\n",
    "# If you're not satisfied with the result, Set to True, run again the cell and it will continue training the current model.\n",
    "\n",
    "\n",
    "Training_Epochs= 50\n",
    "\n",
    "# Epoch = Number of steps/images.\n",
    "\n",
    "Learning_Rate= \"3e-6\"\n",
    "\n",
    "# keep it between 1e-6 and 6e-6\n",
    "\n",
    "\n",
    "External_Captions= True\n",
    "\n",
    "# Load the captions from a text file for each instance image.\n",
    "\n",
    "\n",
    "LoRA_Dim = 128\n",
    "\n",
    "# Dimension of the LoRa model, between 64 and 128 is good enough.\n",
    "\n",
    "\n",
    "Resolution= 1024\n",
    "\n",
    "# 1024 is the native resolution.\n",
    "\n",
    "\n",
    "Save_VRAM = False\n",
    "\n",
    "# Use as low as 9.7GB VRAM with Dim = 64, but slightly slower training.\n",
    "\n",
    "#-----------------\n",
    "dbtrainxl(Resume_Training, Training_Epochs, Learning_Rate, LoRA_Dim, False, Resolution, MODEL_NAMExl, SESSION_DIR, INSTANCE_DIR, CAPTIONS_DIR, External_Captions, INSTANCE_NAME, Session_Name, OUTPUT_DIR, 0.03, Save_VRAM)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2751798-508e-47ad-8e54-95188bdab051",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "# Test the Trained Model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1bc48d6-1526-44c6-ab7c-cc1538c7f61c",
   "metadata": {},
   "source": [
    "# ComfyUI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26272665-16de-4042-a7a4-6b9205ff3309",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "Args=\"--listen --port 3000\"\n",
    "\n",
    "\n",
    "Download_SDXL_Model= True\n",
    "\n",
    "\n",
    "Huggingface_token_optional= \"\"\n",
    "\n",
    "# Restore your backed-up Comfy folder by entering your huggingface token, leave it empty to start fresh or continue with the existing sd folder (if any).\n",
    "\n",
    "#--------------------\n",
    "restored=sdcmff(Huggingface_token_optional, MDLPTH, Download_SDXL_Model, restored)\n",
    "!python /workspace/ComfyUI/main.py $Args"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "410520ca-7352-4fc4-907b-cb53f661074e",
   "metadata": {},
   "source": [
    "# A1111"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "351f18d5-f723-4d25-b1ae-1296a22c6d8c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "User = \"\"\n",
    "\n",
    "Password= \"\"\n",
    "\n",
    "# Add credentials to your Gradio interface (optional).\n",
    "\n",
    "Download_SDXL_Model= True\n",
    "\n",
    "\n",
    "Huggingface_token_optional= \"\"\n",
    "\n",
    "# Restore your backed-up SD folder by entering your huggingface token, leave it empty to start fresh or continue with the existing sd folder (if any).\n",
    "\n",
    "#-----------------\n",
    "configf, restoreda=test(MDLPTH, User, Password, Huggingface_token_optional, Download_SDXL_Model, restoreda)\n",
    "!python /workspace/sd/stable-diffusion-webui/webui.py $configf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "093d64a7-3d4e-4197-8075-4ed11c7f0ae8",
   "metadata": {},
   "source": [
    "# Free up space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "370ba58a-d58d-4a80-9575-8c6e094e2626",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Display a list of sessions from which you can remove any session you don't need anymore\n",
    "\n",
    "#-------------------------\n",
    "clean()"
   ]
  }
 ],
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