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[diffusion] feat: support distilled vae generic (#14195)

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Co-authored-by: BBuf <1182563586@qq.com>
Co-authored-by: Mick <mickjagger19@icloud.com>
This commit is contained in:
Dongjie Zou
2025-12-02 21:27:31 -05:00
committed by GitHub
parent 922054079c
commit f764c6910d
10 changed files with 302 additions and 79 deletions
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47
python/sglang/multimodal_gen/runtime/utils/hf_diffusers_utils.py
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@@ -135,33 +135,33 @@ def get_diffusers_component_config(
"""Gets a configuration of a submodule for the given diffusers model.
Args:
model_path: the path of the submodule
model_path: the path of the submodule (can be local path or HuggingFace model ID)
Returns:
The loaded configuration.
"""
# Check if the model path exists
if os.path.exists(model_path):
# tokenizer
config_names = ["generation_config.json"]
# By default, we load config.json, but scheduler_config.json for scheduler
if "scheduler" in model_path:
config_names.append("scheduler_config.json")
else:
config_names.append("config.json")
# Download from HuggingFace Hub if path doesn't exist locally
if not os.path.exists(model_path):
model_path = maybe_download_model(model_path)
config_file_paths = [
os.path.join(model_path, config_name) for config_name in config_names
]
combined_config = reduce(
lambda acc, path: acc | load_dict(path), config_file_paths, {}
)
return combined_config
# tokenizer
config_names = ["generation_config.json"]
# By default, we load config.json, but scheduler_config.json for scheduler
if "scheduler" in model_path:
config_names.append("scheduler_config.json")
else:
raise RuntimeError(f"Diffusers config file not found at {model_path}")
config_names.append("config.json")
config_file_paths = [
os.path.join(model_path, config_name) for config_name in config_names
]
combined_config = reduce(
lambda acc, path: acc | load_dict(path), config_file_paths, {}
)
return combined_config
# Models don't use the same configuration key for determining the maximum
@@ -390,9 +390,10 @@ def maybe_download_model(
logger.info(
"Downloading model snapshot from HF Hub for %s...", model_name_or_path
)
with get_lock(model_name_or_path).acquire(
poll_interval=2
), suppress_other_loggers(not_suppress_on_main_rank=True):
with (
get_lock(model_name_or_path).acquire(poll_interval=2),
suppress_other_loggers(not_suppress_on_main_rank=True),
):
local_path = snapshot_download(
repo_id=model_name_or_path,
ignore_patterns=["*.onnx", "*.msgpack"],