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Use fp16 for intermediate for fp8 weights with --fast if supported.
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@ -741,6 +741,9 @@ def unet_manual_cast(weight_dtype, inference_device, supported_dtypes=[torch.flo
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return None
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return None
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fp16_supported = should_use_fp16(inference_device, prioritize_performance=True)
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fp16_supported = should_use_fp16(inference_device, prioritize_performance=True)
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if PRIORITIZE_FP16 and fp16_supported and torch.float16 in supported_dtypes:
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return torch.float16
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for dt in supported_dtypes:
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for dt in supported_dtypes:
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if dt == torch.float16 and fp16_supported:
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if dt == torch.float16 and fp16_supported:
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return torch.float16
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return torch.float16
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