Skip to content

Allow passing session_options for ORT backend #620

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
anton-l merged 1 commit into from
Sep 23, 2022
Merged

Allow passing session_options for ORT backend #620

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
11 changes: 7 additions & 4 deletions src/diffusers/onnx_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -49,7 +49,7 @@ def __call__(self, **kwargs):
return self.model.run(None, inputs)

@staticmethod
def load_model(path: Union[str, Path], provider=None):
def load_model(path: Union[str, Path], provider=None, sess_options=None):
"""
Loads an ONNX Inference session with an ExecutionProvider. Default provider is `CPUExecutionProvider`

Expand All @@ -63,7 +63,7 @@ def load_model(path: Union[str, Path], provider=None):
logger.info("No onnxruntime provider specified, using CPUExecutionProvider")
provider = "CPUExecutionProvider"

return ort.InferenceSession(path, providers=[provider])
return ort.InferenceSession(path, providers=[provider], sess_options=sess_options)

def _save_pretrained(self, save_directory: Union[str, Path], file_name: Optional[str] = None, **kwargs):
"""
Expand Down Expand Up @@ -117,6 +117,7 @@ def _from_pretrained(
cache_dir: Optional[str] = None,
file_name: Optional[str] = None,
provider: Optional[str] = None,
sess_options: Optional[ort.SessionOptions] = None,
**kwargs,
):
"""
Expand Down Expand Up @@ -146,7 +147,9 @@ def _from_pretrained(
model_file_name = file_name if file_name is not None else ONNX_WEIGHTS_NAME
# load model from local directory
if os.path.isdir(model_id):
model = OnnxRuntimeModel.load_model(os.path.join(model_id, model_file_name), provider=provider)
model = OnnxRuntimeModel.load_model(
os.path.join(model_id, model_file_name), provider=provider, sess_options=sess_options
)
kwargs["model_save_dir"] = Path(model_id)
# load model from hub
else:
Expand All @@ -161,7 +164,7 @@ def _from_pretrained(
)
kwargs["model_save_dir"] = Path(model_cache_path).parent
kwargs["latest_model_name"] = Path(model_cache_path).name
model = OnnxRuntimeModel.load_model(model_cache_path, provider=provider)
model = OnnxRuntimeModel.load_model(model_cache_path, provider=provider, sess_options=sess_options)
return cls(model=model, **kwargs)

@classmethod
Expand Down
2 changes: 2 additions & 0 deletions src/diffusers/pipeline_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -284,6 +284,7 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
revision = kwargs.pop("revision", None)
torch_dtype = kwargs.pop("torch_dtype", None)
provider = kwargs.pop("provider", None)
sess_options = kwargs.pop("sess_options", None)

# 1. Download the checkpoints and configs
# use snapshot download here to get it working from from_pretrained
Expand Down Expand Up @@ -396,6 +397,7 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
loading_kwargs["torch_dtype"] = torch_dtype
if issubclass(class_obj, diffusers.OnnxRuntimeModel):
loading_kwargs["provider"] = provider
loading_kwargs["sess_options"] = sess_options

# check if the module is in a subdirectory
if os.path.isdir(os.path.join(cached_folder, name)):
Expand Down