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revert to use without_autocast()
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@ -54,7 +54,7 @@ def samples_to_images_tensor(sample, approximation=None, model=None):
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else:
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if model is None:
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model = shared.sd_model
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with torch.no_grad(), devices.manual_cast(devices.dtype_vae): # fixes an issue with unstable VAEs that are flaky even in fp32
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with torch.no_grad(), devices.without_autocast(): # fixes an issue with unstable VAEs that are flaky even in fp32
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x_sample = model.decode_first_stage(sample.to(model.first_stage_model.dtype))
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return x_sample
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