nikigoli commited on
Commit
63e6330
1 Parent(s): 1cc5944

printing devices

Browse files
Files changed (1) hide show
  1. app.py +7 -2
app.py CHANGED
@@ -231,10 +231,15 @@ def count(image, text, prompts, state, device):
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  input_image, _ = transform(image, {"exemplars": torch.tensor([])})
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  input_image = input_image.unsqueeze(0).to(device)
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  exemplars = get_box_inputs(prompts["points"])
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- print(exemplars)
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  input_image_exemplars, exemplars = transform(prompts["image"], {"exemplars": torch.tensor(exemplars)})
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  input_image_exemplars = input_image_exemplars.unsqueeze(0).to(device)
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  exemplars = [exemplars["exemplars"].to(device)]
 
 
 
 
 
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  with torch.no_grad():
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  model_output = model(
@@ -316,7 +321,7 @@ def count_main(image, text, prompts, device):
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  input_image, _ = transform(image, {"exemplars": torch.tensor([])})
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  input_image = input_image.unsqueeze(0).to(device)
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  exemplars = get_box_inputs(prompts["points"])
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- print(exemplars)
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  input_image_exemplars, exemplars = transform(prompts["image"], {"exemplars": torch.tensor(exemplars)})
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  input_image_exemplars = input_image_exemplars.unsqueeze(0).to(device)
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  exemplars = [exemplars["exemplars"].to(device)]
 
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  input_image, _ = transform(image, {"exemplars": torch.tensor([])})
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  input_image = input_image.unsqueeze(0).to(device)
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  exemplars = get_box_inputs(prompts["points"])
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+
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  input_image_exemplars, exemplars = transform(prompts["image"], {"exemplars": torch.tensor(exemplars)})
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  input_image_exemplars = input_image_exemplars.unsqueeze(0).to(device)
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  exemplars = [exemplars["exemplars"].to(device)]
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+
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+ print("model device: " + str(model.device))
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+ print("input image device: " + str(input_image.device))
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+ print("input image exemplars device: " + str(input_image_exemplars.device))
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+ print("exemplars device: " + str(exemplars[0].device))
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  with torch.no_grad():
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  model_output = model(
 
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  input_image, _ = transform(image, {"exemplars": torch.tensor([])})
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  input_image = input_image.unsqueeze(0).to(device)
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  exemplars = get_box_inputs(prompts["points"])
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+
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  input_image_exemplars, exemplars = transform(prompts["image"], {"exemplars": torch.tensor(exemplars)})
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  input_image_exemplars = input_image_exemplars.unsqueeze(0).to(device)
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  exemplars = [exemplars["exemplars"].to(device)]