Merge pull request #7199 from maxaudron/feature/configurable-data-dir

Add flag to store user data sepperate from source code
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AUTOMATIC1111 2023-01-28 09:24:40 +03:00 committed by GitHub
commit ce72af87d3
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17 changed files with 46 additions and 39 deletions

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@ -8,7 +8,7 @@ import torch
import modules.face_restoration
import modules.shared
from modules import shared, devices, modelloader
from modules.paths import script_path, models_path
from modules.paths import models_path
# codeformer people made a choice to include modified basicsr library to their project which makes
# it utterly impossible to use it alongside with other libraries that also use basicsr, like GFPGAN.

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@ -7,9 +7,11 @@ import git
from modules import paths, shared
extensions = []
extensions_dir = os.path.join(paths.script_path, "extensions")
extensions_dir = os.path.join(paths.data_path, "extensions")
extensions_builtin_dir = os.path.join(paths.script_path, "extensions-builtin")
if not os.path.exists(extensions_dir):
os.makedirs(extensions_dir)
def active():
return [x for x in extensions if x.enabled]

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@ -6,7 +6,7 @@ import re
from pathlib import Path
import gradio as gr
from modules.shared import script_path
from modules.paths import data_path
from modules import shared, ui_tempdir, script_callbacks
import tempfile
from PIL import Image
@ -289,7 +289,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
def connect_paste(button, paste_fields, input_comp, jsfunc=None):
def paste_func(prompt):
if not prompt and not shared.cmd_opts.hide_ui_dir_config:
filename = os.path.join(script_path, "params.txt")
filename = os.path.join(data_path, "params.txt")
if os.path.exists(filename):
with open(filename, "r", encoding="utf8") as file:
prompt = file.read()

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@ -6,12 +6,11 @@ import facexlib
import gfpgan
import modules.face_restoration
from modules import shared, devices, modelloader
from modules.paths import models_path
from modules import paths, shared, devices, modelloader
model_dir = "GFPGAN"
user_path = None
model_path = os.path.join(models_path, model_dir)
model_path = os.path.join(paths.models_path, model_dir)
model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
have_gfpgan = False
loaded_gfpgan_model = None

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@ -4,8 +4,10 @@ import os.path
import filelock
from modules.paths import data_path
cache_filename = "cache.json"
cache_filename = os.path.join(data_path, "cache.json")
cache_data = None

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@ -12,7 +12,7 @@ from torchvision import transforms
from torchvision.transforms.functional import InterpolationMode
import modules.shared as shared
from modules import devices, paths, lowvram, modelloader, errors
from modules import devices, paths, shared, lowvram, modelloader, errors
blip_image_eval_size = 384
clip_model_name = 'ViT-L/14'

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@ -4,7 +4,15 @@ import sys
import modules.safe
script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
models_path = os.path.join(script_path, "models")
# Parse the --data-dir flag first so we can use it as a base for our other argument default values
parser = argparse.ArgumentParser()
parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",)
cmd_opts_pre = parser.parse_known_args()[0]
data_path = cmd_opts_pre.data_dir
models_path = os.path.join(data_path, "models")
# data_path = cmd_opts_pre.data
sys.path.insert(0, script_path)
# search for directory of stable diffusion in following places

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@ -17,6 +17,7 @@ from modules import devices, prompt_parser, masking, sd_samplers, lowvram, gener
from modules.sd_hijack import model_hijack
from modules.shared import opts, cmd_opts, state
import modules.shared as shared
import modules.paths as paths
import modules.face_restoration
import modules.images as images
import modules.styles
@ -584,7 +585,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if not p.disable_extra_networks:
extra_networks.activate(p, extra_network_data)
with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:
with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file:
processed = Processed(p, [], p.seed, "")
file.write(processed.infotext(p, 0))

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@ -1,16 +1,14 @@
import os
import sys
import traceback
import importlib.util
from types import ModuleType
def load_module(path):
with open(path, "r", encoding="utf8") as file:
text = file.read()
compiled = compile(text, path, 'exec')
module = ModuleType(os.path.basename(path))
exec(compiled, module.__dict__)
module_spec = importlib.util.spec_from_file_location(os.path.basename(path), path)
module = importlib.util.module_from_spec(module_spec)
module_spec.loader.exec_module(module)
return module

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@ -12,13 +12,13 @@ import ldm.modules.midas as midas
from ldm.util import instantiate_from_config
from modules import shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config
from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config
from modules.paths import models_path
from modules.sd_hijack_inpainting import do_inpainting_hijack
from modules.timer import Timer
model_dir = "Stable-diffusion"
model_path = os.path.abspath(os.path.join(models_path, model_dir))
model_path = os.path.abspath(os.path.join(paths.models_path, model_dir))
checkpoints_list = {}
checkpoint_alisases = {}
@ -307,7 +307,7 @@ def enable_midas_autodownload():
location automatically.
"""
midas_path = os.path.join(models_path, 'midas')
midas_path = os.path.join(paths.models_path, 'midas')
# stable-diffusion-stability-ai hard-codes the midas model path to
# a location that differs from where other scripts using this model look.

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@ -3,13 +3,12 @@ import safetensors.torch
import os
import collections
from collections import namedtuple
from modules import shared, devices, script_callbacks, sd_models
from modules.paths import models_path
from modules import paths, shared, devices, script_callbacks, sd_models
import glob
from copy import deepcopy
vae_path = os.path.abspath(os.path.join(models_path, "VAE"))
vae_path = os.path.abspath(os.path.join(paths.models_path, "VAE"))
vae_ignore_keys = {"model_ema.decay", "model_ema.num_updates"}
vae_dict = {}

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@ -14,7 +14,7 @@ import modules.memmon
import modules.styles
import modules.devices as devices
from modules import localization, extensions, script_loading, errors, ui_components, shared_items
from modules.paths import models_path, script_path
from modules.paths import models_path, script_path, data_path
demo = None
@ -25,6 +25,7 @@ sd_model_file = os.path.join(script_path, 'model.ckpt')
default_sd_model_file = sd_model_file
parser = argparse.ArgumentParser()
parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",)
parser.add_argument("--config", type=str, default=sd_default_config, help="path to config which constructs model",)
parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",)
parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to directory with stable diffusion checkpoints")
@ -35,7 +36,7 @@ parser.add_argument("--no-half", action='store_true', help="do not switch the mo
parser.add_argument("--no-half-vae", action='store_true', help="do not switch the VAE model to 16-bit floats")
parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
parser.add_argument("--embeddings-dir", type=str, default=os.path.join(script_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
parser.add_argument("--embeddings-dir", type=str, default=os.path.join(data_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'textual_inversion_templates'), help="directory with textual inversion templates")
parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory")
@ -74,16 +75,16 @@ parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for sp
parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)
parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False)
parser.add_argument("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(script_path, 'ui-config.json'))
parser.add_argument("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(data_path, 'ui-config.json'))
parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide directory configuration from webui", default=False)
parser.add_argument("--freeze-settings", action='store_true', help="disable editing settings", default=False)
parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(script_path, 'config.json'))
parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(data_path, 'config.json'))
parser.add_argument("--gradio-debug", action='store_true', help="launch gradio with --debug option")
parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None)
parser.add_argument("--gradio-img2img-tool", type=str, help='does not do anything')
parser.add_argument("--gradio-inpaint-tool", type=str, help="does not do anything")
parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last")
parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(script_path, 'styles.csv'))
parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(data_path, 'styles.csv'))
parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False)
parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None)
parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False)

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@ -6,8 +6,7 @@ import sys
import tqdm
import time
from modules import shared, images, deepbooru
from modules.paths import models_path
from modules import paths, shared, images, deepbooru
from modules.shared import opts, cmd_opts
from modules.textual_inversion import autocrop
@ -199,7 +198,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre
dnn_model_path = None
try:
dnn_model_path = autocrop.download_and_cache_models(os.path.join(models_path, "opencv"))
dnn_model_path = autocrop.download_and_cache_models(os.path.join(paths.models_path, "opencv"))
except Exception as e:
print("Unable to load face detection model for auto crop selection. Falling back to lower quality haar method.", e)

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@ -21,7 +21,7 @@ from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_grad
from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing
from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
from modules.paths import script_path
from modules.paths import script_path, data_path
from modules.shared import opts, cmd_opts, restricted_opts
@ -1510,8 +1510,8 @@ def create_ui():
with open(cssfile, "r", encoding="utf8") as file:
css += file.read() + "\n"
if os.path.exists(os.path.join(script_path, "user.css")):
with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:
if os.path.exists(os.path.join(data_path, "user.css")):
with open(os.path.join(data_path, "user.css"), "r", encoding="utf8") as file:
css += file.read() + "\n"
if not cmd_opts.no_progressbar_hiding:

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@ -132,7 +132,7 @@ def install_extension_from_url(dirname, url):
normalized_url = normalize_git_url(url)
assert len([x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url]) == 0, 'Extension with this URL is already installed'
tmpdir = os.path.join(paths.script_path, "tmp", dirname)
tmpdir = os.path.join(paths.data_path, "tmp", dirname)
try:
shutil.rmtree(tmpdir, True)

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@ -11,7 +11,6 @@ from modules import modelloader, shared
LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
NEAREST = (Image.Resampling.NEAREST if hasattr(Image, 'Resampling') else Image.NEAREST)
from modules.paths import models_path
class Upscaler:
@ -39,7 +38,7 @@ class Upscaler:
self.mod_scale = None
if self.model_path is None and self.name:
self.model_path = os.path.join(models_path, self.name)
self.model_path = os.path.join(shared.models_path, self.name)
if self.model_path and create_dirs:
os.makedirs(self.model_path, exist_ok=True)
@ -143,4 +142,4 @@ class UpscalerNearest(Upscaler):
def __init__(self, dirname=None):
super().__init__(False)
self.name = "Nearest"
self.scalers = [UpscalerData("Nearest", None, self)]
self.scalers = [UpscalerData("Nearest", None, self)]

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@ -15,7 +15,6 @@ logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not
from modules import import_hook, errors, extra_networks
from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
from modules.paths import script_path
import torch