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In FluxTextEncoderInvocation, make sure model is locked before loading next model.

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This commit is contained in:
Ryan Dick
2024-12-18 17:12:12 +00:00
parent 7a5dd084ad
commit 612d6b00e3
1 changed files with 4 additions and 9 deletions
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13
invokeai/app/invocations/flux_text_encoder.py
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@@ -70,14 +70,11 @@ class FluxTextEncoderInvocation(BaseInvocation):
)
def _t5_encode(self, context: InvocationContext) -> torch.Tensor:
t5_tokenizer_info = context.models.load(self.t5_encoder.tokenizer)
t5_text_encoder_info = context.models.load(self.t5_encoder.text_encoder)
prompt = [self.prompt]
with (
t5_text_encoder_info as t5_text_encoder,
t5_tokenizer_info as t5_tokenizer,
context.models.load(self.t5_encoder.text_encoder) as t5_text_encoder,
context.models.load(self.t5_encoder.tokenizer) as t5_tokenizer,
):
assert isinstance(t5_text_encoder, T5EncoderModel)
assert isinstance(t5_tokenizer, T5Tokenizer)
@@ -91,14 +88,12 @@ class FluxTextEncoderInvocation(BaseInvocation):
return prompt_embeds
def _clip_encode(self, context: InvocationContext) -> torch.Tensor:
clip_tokenizer_info = context.models.load(self.clip.tokenizer)
clip_text_encoder_info = context.models.load(self.clip.text_encoder)
prompt = [self.prompt]
clip_text_encoder_info = context.models.load(self.clip.text_encoder)
with (
clip_text_encoder_info.model_on_device() as (cached_weights, clip_text_encoder),
clip_tokenizer_info as clip_tokenizer,
context.models.load(self.clip.tokenizer) as clip_tokenizer,
ExitStack() as exit_stack,
):
assert isinstance(clip_text_encoder, CLIPTextModel)