nightfury commited on
Commit
3417b69
1 Parent(s): 7c85a5d

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +6 -8
app.py CHANGED
@@ -56,7 +56,7 @@ def download_image(url):
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  #device = "cpu" #"cuda" if torch.cuda.is_available() else "cpu"
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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- print("The model will be running on :: ", device, "device")
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  # Convert model parameters and buffers to CPU or Cuda
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  model_id_or_path = "CompVis/stable-diffusion-v1-4"
@@ -65,12 +65,11 @@ pipe = StableDiffusionInpaintingPipeline.from_pretrained(
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  revision="fp16",
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  torch_dtype=torch.double, #float16
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  use_auth_token=auth_token
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- )
 
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  #self.register_buffer('n_', ...)
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  print ("torch.backends.mps.is_available: ", torch.backends.mps.is_available())
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- pipe = pipe.to(device)
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-
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  model = CLIPDensePredT(version='ViT-B/16', reduce_dim=64, complex_trans_conv=True)
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  model = model.to(torch.device(device))
@@ -79,8 +78,8 @@ model.eval() #.half()
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  weightsPATH = './clipseg/weights/rd64-uni.pth'
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- state = {'model': model.state_dict()}
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- torch.save(state, weightsPATH)
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  model.load_state_dict(torch.load(weightsPATH, map_location=torch.device(device)), strict=False) #False
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  #model.load_state_dict(torch.load(weightsPATH)['model'])
@@ -89,8 +88,7 @@ print ("Torch load(model) : ", model)
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  print ("Weights : ")
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  # print weights
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  for k, v in model.named_parameters():
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- print(k, v)
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-
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  imgRes = 256
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  #device = "cpu" #"cuda" if torch.cuda.is_available() else "cpu"
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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+ print("The model will be running on :: ", device, " ~device")
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  # Convert model parameters and buffers to CPU or Cuda
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  model_id_or_path = "CompVis/stable-diffusion-v1-4"
 
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  revision="fp16",
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  torch_dtype=torch.double, #float16
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  use_auth_token=auth_token
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+ ).to(device)
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+ #pipe = pipe.to(device)
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  #self.register_buffer('n_', ...)
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  print ("torch.backends.mps.is_available: ", torch.backends.mps.is_available())
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  model = CLIPDensePredT(version='ViT-B/16', reduce_dim=64, complex_trans_conv=True)
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  model = model.to(torch.device(device))
 
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  weightsPATH = './clipseg/weights/rd64-uni.pth'
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+ #state = {'model': model.state_dict()}
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+ #torch.save(state, weightsPATH)
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  model.load_state_dict(torch.load(weightsPATH, map_location=torch.device(device)), strict=False) #False
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  #model.load_state_dict(torch.load(weightsPATH)['model'])
 
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  print ("Weights : ")
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  # print weights
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  for k, v in model.named_parameters():
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+ print(k, v)
 
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  imgRes = 256
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