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Author SHA1 Message Date
Dave Lage
450a83302b Merge 24ab4c0c4a into fa53f71ec0 2026-04-05 01:17:08 +00:00
rockerBOO
24ab4c0c4a Support loading more checkpoint types 2025-03-26 16:35:04 -04:00
rockerBOO
c0f2808763 Support more checkpoint files for flux 2025-03-26 16:34:47 -04:00
2 changed files with 153 additions and 6 deletions

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@@ -1,5 +1,7 @@
import json import json
import os import os
from pathlib import Path
import re
from dataclasses import replace from dataclasses import replace
from typing import List, Optional, Tuple, Union from typing import List, Optional, Tuple, Union
@@ -26,6 +28,63 @@ MODEL_NAME_SCHNELL = "schnell"
MODEL_VERSION_CHROMA = "chroma" MODEL_VERSION_CHROMA = "chroma"
def get_checkpoint_paths(ckpt_path: str | Path):
"""
Get checkpoint paths for flux models
- huggingface directory structure
- huggingface sharded safetensors files
- in transformer directory
- plain directory
- single safetensor files
"""
if not isinstance(ckpt_path, Path):
# Convert to Path object
ckpt_path = Path(ckpt_path)
# If ckpt_path is a directory
if ckpt_path.is_dir():
# List to store potential checkpoint paths
potential_paths = []
# Check for files directly in the directory
potential_paths.extend(ckpt_path.glob('*.safetensors'))
# Check for files in the transformer subdirectory
transformer_path = ckpt_path / 'transformer'
if transformer_path.is_dir():
potential_paths.extend(transformer_path.glob('*.safetensors'))
# Filter and expand multi-part checkpoint paths
checkpoint_paths = []
for path in potential_paths:
# If it's a multi-part checkpoint
if '-of-' in path.name:
# Use regex to extract parts
match = re.search(r'(.+?)-(\d+)-of-(\d+)', path.name)
if match:
base_name, current_part, total_parts = match.groups()
# Generate all part paths
part_paths = [
path.with_name(f'{base_name}-{i:05d}-of-{int(total_parts):05d}.safetensors')
for i in range(1, int(total_parts) + 1)
]
checkpoint_paths.extend(part_paths)
else:
# Single file checkpoint
checkpoint_paths.append(path)
# Remove duplicates while preserving order
checkpoint_paths = list(dict.fromkeys(checkpoint_paths))
else:
# If ckpt_path is a single file
checkpoint_paths = [ckpt_path]
return checkpoint_paths
def analyze_checkpoint_state(ckpt_path: str) -> Tuple[bool, bool, Tuple[int, int], List[str]]: def analyze_checkpoint_state(ckpt_path: str) -> Tuple[bool, bool, Tuple[int, int], List[str]]:
""" """
チェックポイントの状態を分析し、DiffusersかBFLか、devかschnellか、ブロック数を計算して返す。 チェックポイントの状態を分析し、DiffusersかBFLか、devかschnellか、ブロック数を計算して返す。
@@ -43,12 +102,7 @@ def analyze_checkpoint_state(ckpt_path: str) -> Tuple[bool, bool, Tuple[int, int
# check the state dict: Diffusers or BFL, dev or schnell, number of blocks # check the state dict: Diffusers or BFL, dev or schnell, number of blocks
logger.info(f"Checking the state dict: Diffusers or BFL, dev or schnell") logger.info(f"Checking the state dict: Diffusers or BFL, dev or schnell")
if os.path.isdir(ckpt_path): # if ckpt_path is a directory, it is Diffusers ckpt_paths = get_checkpoint_paths(ckpt_path)
ckpt_path = os.path.join(ckpt_path, "transformer", "diffusion_pytorch_model-00001-of-00003.safetensors")
if "00001-of-00003" in ckpt_path:
ckpt_paths = [ckpt_path.replace("00001-of-00003", f"0000{i}-of-00003") for i in range(1, 4)]
else:
ckpt_paths = [ckpt_path]
keys = [] keys = []
for ckpt_path in ckpt_paths: for ckpt_path in ckpt_paths:

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@@ -0,0 +1,93 @@
import pytest
from pathlib import Path
import tempfile
from library.flux_utils import get_checkpoint_paths
def test_get_checkpoint_paths():
# Create a temporary directory for testing
with tempfile.TemporaryDirectory() as temp_dir:
temp_path = Path(temp_dir)
# Scenario 1: Single safetensors file in root directory
single_file = temp_path / "model.safetensors"
single_file.touch()
paths = get_checkpoint_paths(str(single_file))
assert len(paths) == 1
assert paths[0] == single_file
def test_multiple_root_checkpoint_paths():
"""
Multiple single safetensors files in root directory
"""
with tempfile.TemporaryDirectory() as temp_dir:
temp_path = Path(temp_dir)
# Scenario 2:
file1 = temp_path / "model1.safetensors"
file2 = temp_path / "model2.safetensors"
file1.touch()
file2.touch()
paths = get_checkpoint_paths(temp_path)
assert len(paths) == 2
assert set(paths) == {file1, file2}
def test_multipart_sharded_checkpoint():
with tempfile.TemporaryDirectory() as temp_dir:
temp_path = Path(temp_dir)
# Scenario 3: Sharded multi-part checkpoint
# Create sharded checkpoint files
base_name = "diffusion_pytorch_model"
total_parts = 3
for i in range(1, total_parts + 1):
(temp_path / f"{base_name}-{i:05d}-of-{total_parts:05d}.safetensors").touch()
paths = get_checkpoint_paths(temp_path)
assert len(paths) == total_parts
# Check if all expected part paths are present
expected_paths = [temp_path / f"{base_name}-{i:05d}-of-{total_parts:05d}.safetensors" for i in range(1, total_parts + 1)]
assert set(paths) == set(expected_paths)
def test_transformer_model_dir():
with tempfile.TemporaryDirectory() as temp_dir:
temp_path = Path(temp_dir)
transformer_dir = temp_path / "transformer"
transformer_dir.mkdir()
transformer_file = transformer_dir / "diffusion_pytorch_model.safetensors"
transformer_file.touch()
paths = get_checkpoint_paths(temp_path)
assert transformer_file in paths
def test_mixed_files_sharded_checkpoints():
with tempfile.TemporaryDirectory() as temp_dir:
temp_path = Path(temp_dir)
# Scenario 5: Mixed files and sharded checkpoints
mixed_dir = temp_path / "mixed"
mixed_dir.mkdir()
# Create a single file
(mixed_dir / "single_model.safetensors").touch()
# Create sharded checkpoint
base_name = "diffusion_pytorch_model"
total_parts = 2
for i in range(1, total_parts + 1):
(mixed_dir / f"{base_name}-{i:05d}-of-{total_parts:05d}.safetensors").touch()
paths = get_checkpoint_paths(mixed_dir)
assert len(paths) == total_parts + 1
# Verify correct handling of Path and str inputs
path_input = mixed_dir
str_input = str(mixed_dir)
path_paths = get_checkpoint_paths(path_input)
str_paths = get_checkpoint_paths(str_input)
assert set(path_paths) == set(str_paths)