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Add checkpoint listing functionality in app.py to track and display model checkpoints during training. Update run_training to yield checkpoint information and enhance Gradio UI with checkpoint file outputs for improved user experience.
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#!/usr/bin/env python3
import os
import re
import shutil
import subprocess
import sys
import tempfile
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Any, Tuple
import time
import json
import gradio as gr
import spaces
# Local modules
from download_qwen_image_models import download_all_models, DEFAULT_MODELS_DIR
# Defaults matching train_QIE.sh expectations
DEFAULT_DATA_ROOT = "/data"
DEFAULT_IMAGE_FOLDER = "image"
DEFAULT_OUTPUT_DIR_BASE = "/auto/train_LoRA"
DEFAULT_DATASET_CONFIG = "/auto/dataset_QIE.toml"
DEFAULT_MODELS_ROOT = DEFAULT_MODELS_DIR # "/Qwen-Image_models"
WORKSPACE_AUTO_DIR = "/auto"
# musubi-tuner settings
DEFAULT_MUSUBI_TUNER_DIR = os.environ.get("MUSUBI_TUNER_DIR", "/musubi-tuner")
DEFAULT_MUSUBI_TUNER_REPO = os.environ.get(
"MUSUBI_TUNER_REPO", "https://github.com/kohya-ss/musubi-tuner.git"
)
TRAINING_DIR = Path(__file__).resolve().parent
# Runtime-resolved paths with fallbacks for non-root environments
MUSUBI_TUNER_DIR_RUNTIME = DEFAULT_MUSUBI_TUNER_DIR
MODELS_ROOT_RUNTIME = DEFAULT_MODELS_ROOT
AUTO_DIR_RUNTIME = WORKSPACE_AUTO_DIR
DATA_ROOT_RUNTIME = DEFAULT_DATA_ROOT
def _bash_quote(s: str) -> str:
"""Return a POSIX-safe single-quoted string literal representing s."""
if s is None:
return "''"
return "'" + str(s).replace("'", "'\"'\"'") + "'"
def _ensure_workspace_auto_files() -> None:
"""Ensure /workspace/auto has required helper files from this repo.
Copies training/create_image_caption_json.py and training/dataset_QIE.toml
into /workspace/auto so that train_QIE.sh can run unmodified.
"""
global AUTO_DIR_RUNTIME
try:
os.makedirs(AUTO_DIR_RUNTIME, exist_ok=True)
except PermissionError:
home_auto = os.path.join(os.path.expanduser("~"), "auto")
os.makedirs(home_auto, exist_ok=True)
AUTO_DIR_RUNTIME = home_auto # type: ignore
src_py = TRAINING_DIR / "create_image_caption_json.py"
src_toml = TRAINING_DIR / "dataset_QIE.toml"
dst_py = Path(AUTO_DIR_RUNTIME) / "create_image_caption_json.py"
dst_toml = Path(AUTO_DIR_RUNTIME) / "dataset_QIE.toml"
try:
shutil.copy2(src_py, dst_py)
except Exception:
pass
try:
if src_toml.exists():
shutil.copy2(src_toml, dst_toml)
except Exception:
pass
def _ensure_dir_writable(path: str) -> str:
try:
os.makedirs(path, exist_ok=True)
return path
except PermissionError:
home_path = os.path.join(os.path.expanduser("~"), os.path.basename(path.strip("/\\")))
os.makedirs(home_path, exist_ok=True)
return home_path
def _ensure_data_root(candidate: Optional[str]) -> str:
root = (candidate or DEFAULT_DATA_ROOT).strip() or DEFAULT_DATA_ROOT
try:
os.makedirs(root, exist_ok=True)
return root
except PermissionError:
home_root = os.path.join(os.path.expanduser("~"), "data")
os.makedirs(home_root, exist_ok=True)
return home_root
def _extract_paths(files: Any) -> List[Tuple[str, str]]:
"""Extract a list of (abs_path, orig_basename) from Gradio Files input.
Supports various gradio return shapes across versions.
"""
out: List[Tuple[str, str]] = []
if not files:
return out
# Gradio Files often returns a list
if isinstance(files, (list, tuple)):
items = files
else:
items = [files]
for item in items:
p: Optional[str] = None
orig: Optional[str] = None
# dict-like
if isinstance(item, dict):
p = item.get("path") or item.get("name") or item.get("file")
orig = item.get("orig_name") or item.get("name")
else:
# object with attributes
p = getattr(item, "name", None) or getattr(item, "path", None) or str(item)
# best-effort original name attribute
orig = getattr(item, "orig_name", None) or os.path.basename(p) if p else None
if p:
abs_p = os.path.abspath(p)
out.append((abs_p, os.path.basename(orig or abs_p)))
return out
def _norm_key(filename: str, prefix: str, suffix: str) -> str:
stem = os.path.splitext(os.path.basename(filename))[0]
if prefix and stem.startswith(prefix):
stem = stem[len(prefix):]
if suffix and stem.endswith(suffix):
stem = stem[: -len(suffix)]
return stem
def _copy_uploads(
uploads: List[Tuple[str, str]], dest_dir: str, rename_to: Optional[List[str]] = None
) -> List[str]:
os.makedirs(dest_dir, exist_ok=True)
used_names: List[str] = []
for idx, (src, orig) in enumerate(uploads):
# Determine target stem
if rename_to and idx < len(rename_to):
stem = os.path.splitext(rename_to[idx])[0]
else:
stem = os.path.splitext(orig)[0]
dst_name = f"{stem}.png"
# ensure unique within this batch
final_name = dst_name
dup_idx = 1
while final_name in used_names:
final_name = f"{stem}_{dup_idx}.png"
dup_idx += 1
dst_path = os.path.join(dest_dir, final_name)
# Convert to PNG during save
try:
try:
from PIL import Image # type: ignore
with Image.open(src) as img:
img.save(dst_path, format="PNG")
except Exception:
# Fallback: copy then rename
shutil.copy2(src, dst_path)
except Exception:
# Last resort
shutil.copy(src, dst_path)
used_names.append(final_name)
return used_names
def _list_checkpoints(out_dir: str, limit: int = 20) -> List[str]:
try:
if not out_dir or not os.path.isdir(out_dir):
return []
items: List[Tuple[float, str]] = []
for root, _, files in os.walk(out_dir):
for fn in files:
if fn.lower().endswith('.safetensors'):
full = os.path.join(root, fn)
try:
items.append((os.path.getmtime(full), full))
except Exception:
pass
items.sort(reverse=True)
return [p for _, p in items[:limit]]
except Exception:
return []
def _prepare_script(
dataset_name: str,
caption: str,
data_root: str,
image_folder: str,
control_folders: List[Optional[str]],
models_root: str,
output_dir_base: Optional[str] = None,
dataset_config: Optional[str] = None,
override_max_epochs: Optional[int] = None,
override_save_every: Optional[int] = None,
override_run_name: Optional[str] = None,
main_prefix: Optional[str] = None,
main_suffix: Optional[str] = None,
control_prefixes: Optional[List[Optional[str]]] = None,
control_suffixes: Optional[List[Optional[str]]] = None,
) -> Path:
"""Create a temporary copy of train_QIE.sh with injected variables.
Only variables that must vary per-run are replaced. The rest of the script
remains as-is to preserve behavior.
"""
src = TRAINING_DIR / "train_QIE.sh"
txt = src.read_text(encoding="utf-8")
# Replace core variables
replacements = {
r"^DATA_ROOT=\".*\"": f"DATA_ROOT={_bash_quote(data_root)}",
r"^DATASET_NAME=\".*\"": f"DATASET_NAME={_bash_quote(dataset_name)}",
r"^CAPTION=\".*\"": f"CAPTION={_bash_quote(caption)}",
r"^IMAGE_FOLDER=\".*\"": f"IMAGE_FOLDER={_bash_quote(image_folder)}",
}
if output_dir_base:
replacements[r"^OUTPUT_DIR_BASE=\".*\""] = (
f"OUTPUT_DIR_BASE={_bash_quote(output_dir_base)}"
)
if dataset_config:
replacements[r"^DATASET_CONFIG=\".*\""] = (
f"DATASET_CONFIG={_bash_quote(dataset_config)}"
)
for pat, val in replacements.items():
txt = re.sub(pat, val, txt, flags=re.MULTILINE)
# Inject CONTROL_FOLDER_i if provided (uncomment/override or append)
for i in range(8):
val = control_folders[i] if i < len(control_folders) else None
if not val:
continue
# Try to replace commented placeholder first
pattern = rf"^#\s*CONTROL_FOLDER_{i}=\".*\""
if re.search(pattern, txt, flags=re.MULTILINE):
txt = re.sub(
pattern,
f"CONTROL_FOLDER_{i}={_bash_quote(val)}",
txt,
flags=re.MULTILINE,
)
else:
# Append after IMAGE_FOLDER definition
txt = re.sub(
r"^(IMAGE_FOLDER=.*)$",
rf"\1\nCONTROL_FOLDER_{i}={_bash_quote(val)}",
txt,
count=1,
flags=re.MULTILINE,
)
# Point model paths to the selected models_root
def _replace_model_path(txt: str, key: str, rel: str) -> str:
return re.sub(
rf"--{key} \"[^\"]+\"",
f"--{key} \"{models_root.rstrip('/')}/{rel}\"",
txt,
)
txt = _replace_model_path(txt, "vae", "vae/diffusion_pytorch_model.safetensors")
txt = _replace_model_path(txt, "text_encoder", "text_encoder/qwen_2.5_vl_7b.safetensors")
txt = _replace_model_path(txt, "dit", "dit/qwen_image_edit_2509_bf16.safetensors")
# Replace working dir for metadata generation to runtime /auto
txt = re.sub(r"^cd\s+/workspace/auto\s*$", f"cd {AUTO_DIR_RUNTIME}", txt, flags=re.MULTILINE)
# Ensure musubi-tuner path matches runtime location
txt = re.sub(r"^cd\s+/musubi-tuner\s*$", f"cd {re.escape(MUSUBI_TUNER_DIR_RUNTIME)}", txt, flags=re.MULTILINE)
# ZeroGPU compatibility: avoid spawning via 'accelerate launch'.
# Run the training module directly in-process so GPU stays attached
# to the same Python request context.
txt = re.sub(
r"\baccelerate\s+launch\s+src/musubi_tuner/qwen_image_train_network.py",
r"python src/musubi_tuner/qwen_image_train_network.py",
txt,
flags=re.MULTILINE,
)
# Optionally override epochs and save frequency for ZeroGPU time slicing
if override_max_epochs is not None and override_max_epochs > 0:
txt = re.sub(r"--max_train_epochs\s+\d+",
f"--max_train_epochs {override_max_epochs}", txt)
if override_save_every is not None and override_save_every > 0:
txt = re.sub(r"--save_every_n_epochs\s+\d+",
f"--save_every_n_epochs {override_save_every}", txt)
if override_run_name:
txt = re.sub(r"^RUN_NAME=.*$", f"RUN_NAME={_bash_quote(override_run_name)}", txt, flags=re.MULTILINE)
# Inject prefix/suffix flags for metadata creation
extra_lines: List[str] = []
if (main_prefix or ""):
extra_lines.append(f" --main_prefix {_bash_quote(main_prefix)} \\")
if (main_suffix or ""):
extra_lines.append(f" --main_suffix {_bash_quote(main_suffix)} \\")
for i in range(8):
pre = control_prefixes[i] if (control_prefixes and i < len(control_prefixes)) else None
suf = control_suffixes[i] if (control_suffixes and i < len(control_suffixes)) else None
if pre:
extra_lines.append(f" --control_prefix_{i} {_bash_quote(pre)} \\")
if suf:
extra_lines.append(f" --control_suffix_{i} {_bash_quote(suf)} \\")
if extra_lines:
extra_block = "\n".join(extra_lines)
txt = re.sub(r'^(\s*)"\$\{CONTROL_ARGS\[@\]\}"', rf"{extra_block}\n\1\"\${{CONTROL_ARGS[@]}}\"", txt, flags=re.MULTILINE)
# Write to a temp file alongside this repo for easier inspection
run_dir = TRAINING_DIR / ".gradio_runs"
run_dir.mkdir(parents=True, exist_ok=True)
tmp = run_dir / f"train_QIE_run_{os.getpid()}.sh"
tmp.write_text(txt, encoding="utf-8", newline="\n")
try:
os.chmod(tmp, 0o755)
except Exception:
pass
return tmp
def _pick_shell() -> str:
for sh in ("bash", "sh"):
if shutil.which(sh):
return sh
raise RuntimeError("No POSIX shell found. Please install bash or sh.")
def _is_git_repo(path: str) -> bool:
try:
out = subprocess.run(
["git", "-C", path, "rev-parse", "--is-inside-work-tree"],
capture_output=True,
text=True,
check=False,
)
return out.returncode == 0 and out.stdout.strip() == "true"
except Exception:
return False
def _startup_clone_musubi_tuner() -> None:
global MUSUBI_TUNER_DIR_RUNTIME
target = MUSUBI_TUNER_DIR_RUNTIME
repo = DEFAULT_MUSUBI_TUNER_REPO
parent = os.path.dirname(target.rstrip("/\\")) or "/"
try:
os.makedirs(parent, exist_ok=True)
except PermissionError:
# Fallback to home directory
target = os.path.join(os.path.expanduser("~"), "musubi-tuner")
MUSUBI_TUNER_DIR_RUNTIME = target
os.makedirs(os.path.dirname(target), exist_ok=True)
except Exception:
pass
if os.path.isdir(target) and _is_git_repo(target):
print(f"[QIE] musubi-tuner exists at {target}; pulling latest...")
try:
subprocess.run(["git", "-C", target, "fetch", "--all", "--prune"], check=False)
subprocess.run(["git", "-C", target, "pull", "--ff-only"], check=False)
except Exception as e:
print(f"[QIE] git pull failed: {e}")
return
if os.path.exists(target) and not _is_git_repo(target):
print(f"[QIE] Warning: {target} exists and is not a git repo. Skipping clone.")
return
print(f"[QIE] Cloning musubi-tuner into {target} from {repo} ...")
try:
subprocess.run(["git", "clone", "--depth", "1", repo, target], check=True)
print("[QIE] Clone completed.")
except subprocess.CalledProcessError as e:
print(f"[QIE] Clone failed at {target}: {e}")
# Last-chance fallback into home
if not target.startswith(os.path.expanduser("~")):
fallback = os.path.join(os.path.expanduser("~"), "musubi-tuner")
print(f"[QIE] Retrying clone into {fallback}...")
try:
subprocess.run(["git", "clone", "--depth", "1", repo, fallback], check=True)
MUSUBI_TUNER_DIR_RUNTIME = fallback
print("[QIE] Clone completed in fallback.")
except Exception as e2:
print(f"[QIE] Clone failed in fallback as well: {e2}")
def _run_pip(args: List[str], cwd: Optional[str] = None) -> None:
cmd = [sys.executable, "-m", "pip"] + args
try:
print(f"[QIE] pip {' '.join(args)} (cwd={cwd or os.getcwd()})")
subprocess.run(cmd, check=True, cwd=cwd)
except subprocess.CalledProcessError as e:
print(f"[QIE] pip failed: {e}")
def _startup_install_musubi_deps() -> None:
repo_dir = MUSUBI_TUNER_DIR_RUNTIME
if not os.path.isdir(repo_dir):
print(f"[QIE] Skip deps: musubi-tuner not found at {repo_dir}")
return
# Upgrade basic build tooling (best-effort)
try:
_run_pip(["install", "-U", "pip", "setuptools", "wheel"])
except Exception:
pass
# Optional Torch extra via env: MUSUBI_TUNER_TORCH_EXTRA=cu124|cu128
extra = os.environ.get("MUSUBI_TUNER_TORCH_EXTRA", "").strip()
editable_spec = "." if not extra else f".[{extra}]"
# Install musubi-tuner in editable mode to expose entrypoints and deps
try:
_run_pip(["install", "-e", editable_spec], cwd=repo_dir)
except Exception:
# Fallback: plain install without editable
try:
_run_pip(["install", editable_spec], cwd=repo_dir)
except Exception:
print("[QIE] WARN: musubi-tuner installation failed. Continuing.")
@spaces.GPU
def run_training(
output_name: str,
caption: str,
image_uploads: Any,
main_prefix: str,
main_suffix: str,
control0_uploads: Any,
ctrl0_prefix: str,
ctrl0_suffix: str,
control1_uploads: Any,
ctrl1_prefix: str,
ctrl1_suffix: str,
control2_uploads: Any,
ctrl2_prefix: str,
ctrl2_suffix: str,
control3_uploads: Any,
ctrl3_prefix: str,
ctrl3_suffix: str,
control4_uploads: Any,
ctrl4_prefix: str,
ctrl4_suffix: str,
control5_uploads: Any,
ctrl5_prefix: str,
ctrl5_suffix: str,
control6_uploads: Any,
ctrl6_prefix: str,
ctrl6_suffix: str,
control7_uploads: Any,
ctrl7_prefix: str,
ctrl7_suffix: str,
max_epochs: int,
save_every: int,
) -> Iterable[tuple]:
# Basic validation
log_buf = ""
ckpts: List[str] = []
if not output_name.strip():
log_buf += "[ERROR] OUTPUT NAME is required.\n"
yield (log_buf, ckpts, None)
return
if not caption.strip():
log_buf += "[ERROR] CAPTION is required.\n"
yield (log_buf, ckpts, None)
return
# Ensure /auto holds helper files expected by the script
_ensure_workspace_auto_files()
# Resolve data root and create dataset directories (auto-decide)
global DATA_ROOT_RUNTIME
DATA_ROOT_RUNTIME = _ensure_data_root(None)
# Auto-generate dataset directory name
import time
ds_name = f"dataset_{int(time.time())}"
ds_dir = os.path.join(DATA_ROOT_RUNTIME, ds_name)
img_folder_name = DEFAULT_IMAGE_FOLDER
img_dir = os.path.join(ds_dir, img_folder_name)
os.makedirs(img_dir, exist_ok=True)
# Ingest uploads into dataset folders
base_files = _extract_paths(image_uploads)
if not base_files:
log_buf += "[ERROR] No images uploaded for IMAGE_FOLDER.\n"
yield (log_buf, ckpts, None)
return
base_filenames = _copy_uploads(base_files, img_dir)
log_buf += f"[QIE] Copied {len(base_filenames)} base images to {img_dir}\n"
yield (log_buf, ckpts, None)
# Prepare control sets
control_upload_sets = [
_extract_paths(control0_uploads),
_extract_paths(control1_uploads),
_extract_paths(control2_uploads),
_extract_paths(control3_uploads),
_extract_paths(control4_uploads),
_extract_paths(control5_uploads),
_extract_paths(control6_uploads),
_extract_paths(control7_uploads),
]
# Require control_0; others optional
if not control_upload_sets[0]:
log_buf += "[ERROR] control_0 images are required.\n"
yield (log_buf, ckpts, None)
return
control_dirs: List[Optional[str]] = []
for i, uploads in enumerate(control_upload_sets):
if not uploads:
control_dirs.append(None)
continue
folder_name = f"control_{i}"
cdir = os.path.join(ds_dir, folder_name)
os.makedirs(cdir, exist_ok=True)
# Simply copy; name matching will be handled by create_image_caption_json.py
_copy_uploads(uploads, cdir)
control_dirs.append(folder_name)
log_buf += f"[QIE] Copied {len(uploads)} control_{i} images to {cdir}\n"
yield (log_buf, ckpts, None)
# Metadata.jsonl will be generated by create_image_caption_json.py in train_QIE.sh
# Prepare script with user parameters
control_folders = [
(control_dirs[i] if control_dirs[i] else None)
for i in range(8)
]
# Decide dataset_config path with fallback to runtime auto dir
ds_conf = str(Path(AUTO_DIR_RUNTIME) / "dataset_QIE.toml")
# Resolve models_root and set output_dir_base to the unique dataset dir
models_root = MODELS_ROOT_RUNTIME
out_base = ds_dir
try:
os.makedirs(out_base, exist_ok=True)
except Exception:
pass
tmp_script = _prepare_script(
dataset_name=ds_name,
caption=caption,
data_root=DATA_ROOT_RUNTIME,
image_folder=img_folder_name,
control_folders=control_folders,
models_root=models_root,
output_dir_base=out_base,
dataset_config=ds_conf,
override_max_epochs=max_epochs if max_epochs and max_epochs > 0 else None,
override_save_every=save_every if save_every and save_every > 0 else None,
override_run_name=output_name.strip(),
main_prefix=(main_prefix or ""),
main_suffix=(main_suffix or ""),
control_prefixes=[ctrl0_prefix, ctrl1_prefix, ctrl2_prefix, ctrl3_prefix, ctrl4_prefix, ctrl5_prefix, ctrl6_prefix, ctrl7_prefix],
control_suffixes=[ctrl0_suffix, ctrl1_suffix, ctrl2_suffix, ctrl3_suffix, ctrl4_suffix, ctrl5_suffix, ctrl6_suffix, ctrl7_suffix],
)
shell = _pick_shell()
log_buf += f"[QIE] Using shell: {shell}\n"
log_buf += f"[QIE] Running script: {tmp_script}\n"
out_dir = os.path.join(out_base, output_name.strip())
ckpts = _list_checkpoints(out_dir)
yield (log_buf, ckpts, None)
# Run and stream output
proc = subprocess.Popen(
[shell, str(tmp_script)],
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
text=True,
bufsize=1,
universal_newlines=True,
)
try:
assert proc.stdout is not None
i = 0
for line in proc.stdout:
log_buf += line
i += 1
if i % 30 == 0:
ckpts = _list_checkpoints(out_dir)
yield (log_buf, ckpts, None)
finally:
code = proc.wait()
# Try to locate latest LoRA file for download
lora_path = None
try:
ckpts = _list_checkpoints(out_dir)
except Exception:
pass
lora_path = ckpts[0] if ckpts else None
log_buf += f"[QIE] Exit code: {code}\n"
yield (log_buf, ckpts, lora_path)
def build_ui() -> gr.Blocks:
with gr.Blocks(title="Qwen-Image-Edit: Trainer") as demo:
gr.Markdown("""
# Qwen-Image-Edit Trainer
""")
with gr.Row():
output_name = gr.Textbox(label="OUTPUT NAME", placeholder="my_lora_output", lines=1)
caption = gr.Textbox(label="CAPTION", placeholder="A photo of ...", lines=2)
with gr.Row():
images_input = gr.File(label="Upload main images", file_count="multiple", type="filepath", scale=3)
try:
with gr.Column(scale=1):
main_prefix = gr.Textbox(label="Main prefix", placeholder="e.g., img_")
main_suffix = gr.Textbox(label="Main suffix", placeholder="e.g., _v2")
except Exception:
# Fallback if Column is unavailable
main_prefix = gr.Textbox(label="Main prefix", placeholder="e.g., img_")
main_suffix = gr.Textbox(label="Main suffix", placeholder="e.g., _v2")
# control_0 is required and shown outside the accordion
with gr.Row():
ctrl0_files = gr.File(label="Upload control_0 images (required)", file_count="multiple", type="filepath", scale=3)
try:
with gr.Column(scale=1):
ctrl0_prefix = gr.Textbox(label="control_0 prefix", placeholder="")
ctrl0_suffix = gr.Textbox(label="control_0 suffix", placeholder="")
except Exception:
ctrl0_prefix = gr.Textbox(label="control_0 prefix", placeholder="")
ctrl0_suffix = gr.Textbox(label="control_0 suffix", placeholder="")
# Optional controls start from 1, accordion closed by default
with gr.Accordion("Optional control images (control_1..control_7)", open=False):
with gr.Row():
ctrl1_files = gr.File(label="Upload control_1 images", file_count="multiple", type="filepath", scale=3)
try:
with gr.Column(scale=1):
ctrl1_prefix = gr.Textbox(label="control_1 prefix", placeholder="")
ctrl1_suffix = gr.Textbox(label="control_1 suffix", placeholder="")
except Exception:
ctrl1_prefix = gr.Textbox(label="control_1 prefix", placeholder="")
ctrl1_suffix = gr.Textbox(label="control_1 suffix", placeholder="")
with gr.Row():
ctrl2_files = gr.File(label="Upload control_2 images", file_count="multiple", type="filepath", scale=3)
try:
with gr.Column(scale=1):
ctrl2_prefix = gr.Textbox(label="control_2 prefix", placeholder="")
ctrl2_suffix = gr.Textbox(label="control_2 suffix", placeholder="")
except Exception:
ctrl2_prefix = gr.Textbox(label="control_2 prefix", placeholder="")
ctrl2_suffix = gr.Textbox(label="control_2 suffix", placeholder="")
with gr.Row():
ctrl3_files = gr.File(label="Upload control_3 images", file_count="multiple", type="filepath", scale=3)
try:
with gr.Column(scale=1):
ctrl3_prefix = gr.Textbox(label="control_3 prefix", placeholder="")
ctrl3_suffix = gr.Textbox(label="control_3 suffix", placeholder="")
except Exception:
ctrl3_prefix = gr.Textbox(label="control_3 prefix", placeholder="")
ctrl3_suffix = gr.Textbox(label="control_3 suffix", placeholder="")
with gr.Row():
ctrl4_files = gr.File(label="Upload control_4 images", file_count="multiple", type="filepath", scale=3)
try:
with gr.Column(scale=1):
ctrl4_prefix = gr.Textbox(label="control_4 prefix", placeholder="")
ctrl4_suffix = gr.Textbox(label="control_4 suffix", placeholder="")
except Exception:
ctrl4_prefix = gr.Textbox(label="control_4 prefix", placeholder="")
ctrl4_suffix = gr.Textbox(label="control_4 suffix", placeholder="")
with gr.Row():
ctrl5_files = gr.File(label="Upload control_5 images", file_count="multiple", type="filepath", scale=3)
try:
with gr.Column(scale=1):
ctrl5_prefix = gr.Textbox(label="control_5 prefix", placeholder="")
ctrl5_suffix = gr.Textbox(label="control_5 suffix", placeholder="")
except Exception:
ctrl5_prefix = gr.Textbox(label="control_5 prefix", placeholder="")
ctrl5_suffix = gr.Textbox(label="control_5 suffix", placeholder="")
with gr.Row():
ctrl6_files = gr.File(label="Upload control_6 images", file_count="multiple", type="filepath", scale=3)
try:
with gr.Column(scale=1):
ctrl6_prefix = gr.Textbox(label="control_6 prefix", placeholder="")
ctrl6_suffix = gr.Textbox(label="control_6 suffix", placeholder="")
except Exception:
ctrl6_prefix = gr.Textbox(label="control_6 prefix", placeholder="")
ctrl6_suffix = gr.Textbox(label="control_6 suffix", placeholder="")
with gr.Row():
ctrl7_files = gr.File(label="Upload control_7 images", file_count="multiple", type="filepath", scale=3)
try:
with gr.Column(scale=1):
ctrl7_prefix = gr.Textbox(label="control_7 prefix", placeholder="")
ctrl7_suffix = gr.Textbox(label="control_7 suffix", placeholder="")
except Exception:
ctrl7_prefix = gr.Textbox(label="control_7 prefix", placeholder="")
ctrl7_suffix = gr.Textbox(label="control_7 suffix", placeholder="")
# Models root / OUTPUT_DIR_BASE / DATASET_CONFIG are auto-resolved at runtime; no user input needed.
run_btn = gr.Button("Start Training", variant="primary")
logs = gr.Textbox(label="Logs", lines=20)
ckpt_files = gr.Files(label="Checkpoints (live)", interactive=False)
lora_file = gr.File(label="Download LoRA (latest)", interactive=False)
with gr.Row():
max_epochs = gr.Number(label="Max epochs (this run)", value=10, precision=0)
save_every = gr.Number(label="Save every N epochs", value=5, precision=0)
run_btn.click(
fn=run_training,
inputs=[
output_name, caption, images_input, main_prefix, main_suffix,
ctrl0_files, ctrl0_prefix, ctrl0_suffix,
ctrl1_files, ctrl1_prefix, ctrl1_suffix,
ctrl2_files, ctrl2_prefix, ctrl2_suffix,
ctrl3_files, ctrl3_prefix, ctrl3_suffix,
ctrl4_files, ctrl4_prefix, ctrl4_suffix,
ctrl5_files, ctrl5_prefix, ctrl5_suffix,
ctrl6_files, ctrl6_prefix, ctrl6_suffix,
ctrl7_files, ctrl7_prefix, ctrl7_suffix,
max_epochs, save_every,
],
outputs=[logs, ckpt_files, lora_file],
)
return demo
def _startup_download_models() -> None:
global MODELS_ROOT_RUNTIME
# Pick a writable models directory
candidate = os.environ.get("QWEN_IMAGE_MODELS_DIR", DEFAULT_MODELS_ROOT)
try:
os.makedirs(candidate, exist_ok=True)
MODELS_ROOT_RUNTIME = candidate
except PermissionError:
MODELS_ROOT_RUNTIME = os.path.join(os.path.expanduser("~"), "Qwen-Image_models")
os.makedirs(MODELS_ROOT_RUNTIME, exist_ok=True)
print(f"[QIE] Ensuring models in: {MODELS_ROOT_RUNTIME}")
try:
download_all_models(MODELS_ROOT_RUNTIME)
except Exception as e:
print(f"[QIE] Model download failed: {e}")
if __name__ == "__main__":
# 1) Ensure musubi-tuner is cloned before anything else
_startup_clone_musubi_tuner()
# 1.1) Install musubi-tuner dependencies (best-effort)
_startup_install_musubi_deps()
# 2) Download models at startup (blocking by design)
_startup_download_models()
# 3) Launch Gradio app
ui = build_ui()
# Limit concurrency (training is heavy). Enable queue for Spaces compatibility.
# Use generic signature to support multiple gradio versions.
try:
ui = ui.queue(max_size=16)
except TypeError:
ui = ui.queue()
# Allow Gradio to serve files saved under our runtime dirs
try:
allowed = [
AUTO_DIR_RUNTIME,
os.path.join(AUTO_DIR_RUNTIME, "train_LoRA"),
DEFAULT_DATA_ROOT,
DATA_ROOT_RUNTIME,
os.path.join(os.path.expanduser("~"), "auto"),
os.path.join(os.path.expanduser("~"), "data"),
]
ui.launch(server_name="0.0.0.0", allowed_paths=allowed)
except TypeError:
# Older gradio without allowed_paths
ui.launch(server_name="0.0.0.0")