theluyuan/DiffSynth-Studio
1
0
Fork 0
mirror of https://github.com/modelscope/DiffSynth-Studio.git synced 2026-03-20 15:48:20 +00:00
Code Issues Packages Projects Releases Wiki Activity

Merge pull request #646 from modelscope/flux-refactor

Browse Source 
Flux refactor
This commit is contained in:
Zhongjie Duan
2025-06-29 18:04:05 +08:00
committed by GitHub
parent 31f9df5e62 44e2eecdf1
commit 3dbe271aab
29 changed files with 2706 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files

1025
diffsynth/pipelines/flux_image_new.py Normal file
View File

File diff suppressed because it is too large Load Diff

36
diffsynth/pipelines/wan_video_new.py
View File

@@ -168,24 +168,48 @@ class ModelConfig:
def download_if_necessary(self, local_model_path="./models", skip_download=False, use_usp=False):
if self.path is None:
if self.model_id is None or self.origin_file_pattern is None:
# Check model_id and origin_file_pattern
if self.model_id is None:
raise ValueError(f"""No valid model files. Please use `ModelConfig(path="xxx")` or `ModelConfig(model_id="xxx/yyy", origin_file_pattern="zzz")`.""")
# Skip if not in rank 0
if use_usp:
import torch.distributed as dist
skip_download = dist.get_rank() != 0
# Check whether the origin path is a folder
if self.origin_file_pattern is None or self.origin_file_pattern == "":
self.origin_file_pattern = ""
allow_file_pattern = None
is_folder = True
elif isinstance(self.origin_file_pattern, str) and self.origin_file_pattern.endswith("/"):
allow_file_pattern = self.origin_file_pattern + "*"
is_folder = True
else:
allow_file_pattern = self.origin_file_pattern
is_folder = False
# Download
if not skip_download:
downloaded_files = glob.glob(self.origin_file_pattern, root_dir=os.path.join(local_model_path, self.model_id))
snapshot_download(
self.model_id,
local_dir=os.path.join(local_model_path, self.model_id),
allow_file_pattern=self.origin_file_pattern,
allow_file_pattern=allow_file_pattern,
ignore_file_pattern=downloaded_files,
local_files_only=False
)
# Let rank 1, 2, ... wait for rank 0
if use_usp:
import torch.distributed as dist
dist.barrier(device_ids=[dist.get_rank()])
self.path = glob.glob(os.path.join(local_model_path, self.model_id, self.origin_file_pattern))
# Return downloaded files
if is_folder:
self.path = os.path.join(local_model_path, self.model_id, self.origin_file_pattern)
else:
self.path = glob.glob(os.path.join(local_model_path, self.model_id, self.origin_file_pattern))
if isinstance(self.path, list) and len(self.path) == 1:
self.path = self.path[0]
@@ -614,11 +638,17 @@ class PipelineUnitRunner:
elif unit.seperate_cfg:
# Positive side
processor_inputs = {name: inputs_posi.get(name_) for name, name_ in unit.input_params_posi.items()}
if unit.input_params is not None:
for name in unit.input_params:
processor_inputs[name] = inputs_shared.get(name)
processor_outputs = unit.process(pipe, **processor_inputs)
inputs_posi.update(processor_outputs)
# Negative side
if inputs_shared["cfg_scale"] != 1:
processor_inputs = {name: inputs_nega.get(name_) for name, name_ in unit.input_params_nega.items()}
if unit.input_params is not None:
for name in unit.input_params:
processor_inputs[name] = inputs_shared.get(name)
processor_outputs = unit.process(pipe, **processor_inputs)
inputs_nega.update(processor_outputs)
else: