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Install sub directories with folders correctly, ensure consistent dtype of tensors in flux pipeline and vae

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This commit is contained in:
Brandon Rising
2024-08-19 13:59:44 -04:00
committed by Brandon
parent 81f0886d6f
commit 4bd7fda694
5 changed files with 7 additions and 9 deletions
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2
invokeai/app/invocations/flux_text_to_image.py
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@ -72,7 +72,7 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
t5_embeddings: torch.Tensor,
):
transformer_info = context.models.load(self.transformer.transformer)
inference_dtype = TorchDevice.choose_torch_dtype()
inference_dtype = torch.bfloat16
# Prepare input noise.
# TODO(ryand): Does the seed behave the same on different devices? Should we re-implement this to always use a

5
invokeai/app/services/model_install/model_install_default.py
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@ -783,8 +783,9 @@ class ModelInstallService(ModelInstallServiceBase):
# So what we do is to synthesize a folder named "sdxl-turbo_vae" here.
if subfolder:
top = Path(remote_files[0].path.parts[0]) # e.g. "sdxl-turbo/"
path_to_remove = top / subfolder.parts[-1] # sdxl-turbo/vae/
path_to_add = Path(f"{top}_{subfolder}")
path_to_remove = top / subfolder # sdxl-turbo/vae/
subfolder_rename = subfolder.name.replace('/', '_').replace('\\', '_')
path_to_add = Path(f"{top}_{subfolder_rename}")
else:
path_to_remove = Path(".")
path_to_add = Path(".")