kamp/IOPaint
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remvoe sd amp.autocast

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Qing 2022-11-04 15:33:59 +08:00
parent dc69276a7d
commit b3cb11f804
1 changed files with 6 additions and 6 deletions
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12
lama_cleaner/model/sd.py
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@ -37,13 +37,14 @@ from lama_cleaner.schema import Config, SDSampler
# return mask # return mask
class CPUTextEncoderWrapper: class CPUTextEncoderWrapper:
def __init__(self, text_encoder): def __init__(self, text_encoder, torch_dtype):
self.text_encoder = text_encoder.to(torch.device('cpu'), non_blocking=True) self.text_encoder = text_encoder.to(torch.device('cpu'), non_blocking=True)
self.text_encoder = self.text_encoder.to(torch.float32, non_blocking=True) self.text_encoder = self.text_encoder.to(torch.float32, non_blocking=True)
self.torch_dtype = torch_dtype
def __call__(self, x): def __call__(self, x):
input_device = x.device input_device = x.device
return [self.text_encoder(x.to(self.text_encoder.device))[0].to(input_device)] return [self.text_encoder(x.to(self.text_encoder.device))[0].to(input_device).to(self.torch_dtype)]
class SD(InpaintModel): class SD(InpaintModel):
@ -61,11 +62,11 @@ class SD(InpaintModel):
)) ))
use_gpu = device == torch.device('cuda') and torch.cuda.is_available() use_gpu = device == torch.device('cuda') and torch.cuda.is_available()
torch_dtype = torch.float16 if use_gpu else torch.float32
self.model = StableDiffusionInpaintPipeline.from_pretrained( self.model = StableDiffusionInpaintPipeline.from_pretrained(
self.model_id_or_path, self.model_id_or_path,
revision="fp16" if use_gpu else "main", revision="fp16" if use_gpu else "main",
torch_dtype=torch.float16 if use_gpu else torch.float32, torch_dtype=torch_dtype,
use_auth_token=kwargs["hf_access_token"], use_auth_token=kwargs["hf_access_token"],
**model_kwargs **model_kwargs
) )
@ -75,11 +76,10 @@ class SD(InpaintModel):
if kwargs['sd_cpu_textencoder']: if kwargs['sd_cpu_textencoder']:
logger.info("Run Stable Diffusion TextEncoder on CPU") logger.info("Run Stable Diffusion TextEncoder on CPU")
self.model.text_encoder = CPUTextEncoderWrapper(self.model.text_encoder) self.model.text_encoder = CPUTextEncoderWrapper(self.model.text_encoder, torch_dtype)
self.callback = kwargs.pop("callback", None) self.callback = kwargs.pop("callback", None)
@torch.cuda.amp.autocast()
def forward(self, image, mask, config: Config): def forward(self, image, mask, config: Config):
"""Input image and output image have same size """Input image and output image have same size
image: [H, W, C] RGB image: [H, W, C] RGB