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@ -45,9 +45,7 @@ class FluxVaeEncodeInvocation(BaseInvocation):
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with vae_info as vae:
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assert isinstance(vae, AutoEncoder)
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vae_dtype = next(iter(vae.state_dict().items()))[1].dtype
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image_tensor = image_tensor.to(
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device=TorchDevice.choose_torch_device(), dtype=vae_dtype
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)
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image_tensor = image_tensor.to(device=TorchDevice.choose_torch_device(), dtype=vae_dtype)
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latents = vae.encode(image_tensor, sample=True, generator=generator)
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return latents
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