SDXL-LoRA-RNPD.ipynb

{
 "cells": [
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   "cell_type": "markdown",
   "id": "b01332d1-1384-4405-8af6-335c768da6e2",
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   "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": null,
   "id": "3d144e06-1f7a-467b-9cf1-452bf773f0ab",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "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": null,
   "id": "2f705bd1-35c9-49bd-84fd-03a1348cbe83",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "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": null,
   "id": "ac69c221-205a-40d2-b42e-6c8d515a43cc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Session_Name = \"Example-Session\"\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": "eea6975c-c56e-4391-89ec-e71ab23f0789",
   "metadata": {},
   "source": [
    "# Instance Images\n",
    "The most important step is to rename the instance pictures to one unique unknown identifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "90213561-6117-4a2e-ab48-4988e2d450df",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Remove_existing_instance_images= True\n",
    "\n",
    "# Set to False to keep the existing instance images if any.\n",
    "\n",
    "\n",
    "IMAGES_FOLDER_OPTIONAL= \"\"\n",
    "\n",
    "# If you prefer to specify directly the folder of the pictures instead of uploading, this will add the pictures to the existing (if any) instance images. Leave EMPTY to upload.\n",
    "\n",
    "\n",
    "Smart_crop_images = True\n",
    "\n",
    "# Automatically crop your input images.\n",
    "\n",
    "Crop_size = 1024\n",
    "\n",
    "# 1024 is the native resolution\n",
    "\n",
    "\n",
    "#--------------------------------------------\n",
    "\n",
    "# Disabled when \"Smart_crop_images\" is set to \"True\"\n",
    "\n",
    "Resize_to_1024_and_keep_aspect_ratio = False\n",
    "\n",
    "# Will resize the smallest dimension to 1024 without cropping while keeping the aspect ratio (make sure you have enough VRAM)\n",
    "\n",
    "\n",
    "# Check out this example for naming : https://i.imgur.com/d2lD3rz.jpeg\n",
    "\n",
    "#-----------------\n",
    "uplder(Remove_existing_instance_images, Smart_crop_images, Crop_size, Resize_to_1024_and_keep_aspect_ratio, IMAGES_FOLDER_OPTIONAL, INSTANCE_DIR, CAPTIONS_DIR)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "982ea644-8902-4bfa-af9b-191d8e079044",
   "metadata": {},
   "source": [
    "# Manual Captioning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c9df5834-e278-4bc9-8161-c1a5bad5f6da",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Open a tool to manually caption the instance images.\n",
    "\n",
    "#-----------------\n",
    "caption(CAPTIONS_DIR, INSTANCE_DIR)"
   ]
  },
  {
   "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": [],
   "source": [
    "# Training Settings\n",
    "\n",
    "# Epoch = Number of steps/images\n",
    "\n",
    "\n",
    "UNet_Training_Epochs= 120\n",
    "\n",
    "UNet_Learning_Rate= \"1e-6\"\n",
    "\n",
    "# Keep the learning rate between 1e-6 and 3e-6\n",
    "\n",
    "\n",
    "Text_Encoder_Training_Epochs= 40\n",
    "\n",
    "# The training is highly affected by this value, a total of 300 steps (not epochs) is enough, set to 0 if enhancing existing concepts\n",
    "\n",
    "Text_Encoder_Learning_Rate= \"1e-6\"\n",
    "\n",
    "# Keep the learning rate at 1e-6 or lower\n",
    "\n",
    "\n",
    "External_Captions= False\n",
    "\n",
    "# Load the captions from a text file for each instance image\n",
    "\n",
    "\n",
    "LoRA_Dim = 64\n",
    "\n",
    "# Dimension of the LoRa model, between 64 and 128 is good enough\n",
    "\n",
    "\n",
    "Save_VRAM = False\n",
    "\n",
    "# Use as low as 10GB VRAM with Dim = 64\n",
    "\n",
    "\n",
    "Intermediary_Save_Epoch = \"[30,60]\"\n",
    "\n",
    "# [30,60] means it will save intermediary models at epoch 30 and epoch 60, you can add as many as you want like [30,60,80,100]\n",
    "\n",
    "\n",
    "#-----------------\n",
    "dbtrainxl(UNet_Training_Epochs, Text_Encoder_Training_Epochs, UNet_Learning_Rate, Text_Encoder_Learning_Rate, LoRA_Dim, False, 1024, MODEL_NAMExl, SESSION_DIR, INSTANCE_DIR, CAPTIONS_DIR, External_Captions, INSTANCE_NAME, Session_Name, OUTPUT_DIR, 0, Save_VRAM, Intermediary_Save_Epoch)"
   ]
  },
  {
   "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 --preview-method auto --force-fp16\"\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, 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",
    "\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, 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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