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revert: inference_mode to no_grad

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blessedcoolant 2023-07-05 16:39:15 +12:00
parent f155887b7d
commit 639d88afd6
3 changed files with 7 additions and 7 deletions
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2
invokeai/app/invocations/compel.py
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@ -56,7 +56,7 @@ class CompelInvocation(BaseInvocation):
}, },
} }
@torch.inference_mode() @torch.no_grad()
def invoke(self, context: InvocationContext) -> CompelOutput: def invoke(self, context: InvocationContext) -> CompelOutput:
tokenizer_info = context.services.model_manager.get_model( tokenizer_info = context.services.model_manager.get_model(
**self.clip.tokenizer.dict(), **self.clip.tokenizer.dict(),

8
invokeai/app/invocations/latent.py
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@ -285,7 +285,7 @@ class TextToLatentsInvocation(BaseInvocation):
# MultiControlNetModel has been refactored out, just need list[ControlNetData] # MultiControlNetModel has been refactored out, just need list[ControlNetData]
return control_data return control_data
@torch.inference_mode() @torch.no_grad()
def invoke(self, context: InvocationContext) -> LatentsOutput: def invoke(self, context: InvocationContext) -> LatentsOutput:
noise = context.services.latents.get(self.noise.latents_name) noise = context.services.latents.get(self.noise.latents_name)
@ -369,7 +369,7 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
}, },
} }
@torch.inference_mode() @torch.no_grad()
def invoke(self, context: InvocationContext) -> LatentsOutput: def invoke(self, context: InvocationContext) -> LatentsOutput:
noise = context.services.latents.get(self.noise.latents_name) noise = context.services.latents.get(self.noise.latents_name)
latent = context.services.latents.get(self.latents.latents_name) latent = context.services.latents.get(self.latents.latents_name)
@ -461,7 +461,7 @@ class LatentsToImageInvocation(BaseInvocation):
}, },
} }
@torch.inference_mode() @torch.no_grad()
def invoke(self, context: InvocationContext) -> ImageOutput: def invoke(self, context: InvocationContext) -> ImageOutput:
latents = context.services.latents.get(self.latents.latents_name) latents = context.services.latents.get(self.latents.latents_name)
@ -599,7 +599,7 @@ class ImageToLatentsInvocation(BaseInvocation):
}, },
} }
@torch.inference_mode() @torch.no_grad()
def invoke(self, context: InvocationContext) -> LatentsOutput: def invoke(self, context: InvocationContext) -> LatentsOutput:
# image = context.services.images.get( # image = context.services.images.get(
# self.image.image_type, self.image.image_name # self.image.image_type, self.image.image_name

4
invokeai/backend/model_management/lora.py
View File

@ -526,7 +526,7 @@ class ModelPatcher:
): ):
original_weights = dict() original_weights = dict()
try: try:
with torch.inference_mode(): with torch.no_grad():
for lora, lora_weight in loras: for lora, lora_weight in loras:
#assert lora.device.type == "cpu" #assert lora.device.type == "cpu"
for layer_key, layer in lora.layers.items(): for layer_key, layer in lora.layers.items():
@ -552,7 +552,7 @@ class ModelPatcher:
yield # wait for context manager exit yield # wait for context manager exit
finally: finally:
with torch.inference_mode(): with torch.no_grad():
for module_key, weight in original_weights.items(): for module_key, weight in original_weights.items():
model.get_submodule(module_key).weight.copy_(weight) model.get_submodule(module_key).weight.copy_(weight)