fix(api): abandon pretrained loader entirely to fix SD upscaling
This commit is contained in:
parent
75f1a2cead
commit
fa38b474f0
|
@ -230,17 +230,32 @@ def load_pipeline(
|
||||||
)
|
)
|
||||||
else:
|
else:
|
||||||
logger.debug(
|
logger.debug(
|
||||||
"loading pretrained SD pipeline for %s", pipeline_class.__name__
|
"assembling SD pipeline for %s", pipeline_class.__name__
|
||||||
)
|
|
||||||
pipe = pipeline_class.from_pretrained(
|
|
||||||
model,
|
|
||||||
provider=device.ort_provider(),
|
|
||||||
sess_options=device.sess_options(),
|
|
||||||
safety_checker=None,
|
|
||||||
torch_dtype=torch_dtype,
|
|
||||||
**components,
|
|
||||||
)
|
)
|
||||||
|
|
||||||
|
if pipeline_class == OnnxStableDiffusionUpscalePipeline:
|
||||||
|
# upscale uses a single VAE
|
||||||
|
pipe = pipeline_class(
|
||||||
|
components["vae"],
|
||||||
|
components["text_encoder"],
|
||||||
|
components["tokenizer"],
|
||||||
|
components["unet"],
|
||||||
|
scheduler,
|
||||||
|
scheduler,
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
pipe = pipeline_class(
|
||||||
|
components["vae_encoder"],
|
||||||
|
components["vae_decoder"],
|
||||||
|
components["text_encoder"],
|
||||||
|
components["tokenizer"],
|
||||||
|
components["unet"],
|
||||||
|
scheduler,
|
||||||
|
None,
|
||||||
|
None,
|
||||||
|
requires_safety_checker=False,
|
||||||
|
)
|
||||||
|
|
||||||
if not server.show_progress:
|
if not server.show_progress:
|
||||||
pipe.set_progress_bar_config(disable=True)
|
pipe.set_progress_bar_config(disable=True)
|
||||||
|
|
||||||
|
|
Loading…
Reference in New Issue