remvoe sd amp.autocast
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@ -37,13 +37,14 @@ from lama_cleaner.schema import Config, SDSampler
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# return mask
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class CPUTextEncoderWrapper:
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def __init__(self, text_encoder):
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def __init__(self, text_encoder, torch_dtype):
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self.text_encoder = text_encoder.to(torch.device('cpu'), non_blocking=True)
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self.text_encoder = self.text_encoder.to(torch.float32, non_blocking=True)
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self.torch_dtype = torch_dtype
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def __call__(self, x):
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input_device = x.device
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return [self.text_encoder(x.to(self.text_encoder.device))[0].to(input_device)]
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return [self.text_encoder(x.to(self.text_encoder.device))[0].to(input_device).to(self.torch_dtype)]
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class SD(InpaintModel):
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@ -61,11 +62,11 @@ class SD(InpaintModel):
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))
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use_gpu = device == torch.device('cuda') and torch.cuda.is_available()
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torch_dtype = torch.float16 if use_gpu else torch.float32
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self.model = StableDiffusionInpaintPipeline.from_pretrained(
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self.model_id_or_path,
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revision="fp16" if use_gpu else "main",
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torch_dtype=torch.float16 if use_gpu else torch.float32,
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torch_dtype=torch_dtype,
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use_auth_token=kwargs["hf_access_token"],
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**model_kwargs
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)
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@ -75,11 +76,10 @@ class SD(InpaintModel):
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if kwargs['sd_cpu_textencoder']:
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logger.info("Run Stable Diffusion TextEncoder on CPU")
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self.model.text_encoder = CPUTextEncoderWrapper(self.model.text_encoder)
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self.model.text_encoder = CPUTextEncoderWrapper(self.model.text_encoder, torch_dtype)
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self.callback = kwargs.pop("callback", None)
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@torch.cuda.amp.autocast()
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def forward(self, image, mask, config: Config):
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"""Input image and output image have same size
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image: [H, W, C] RGB
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