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Descrizione
Enter the chapter number
Ch16
Enter the page number
674
What is the cell's number in the notebook
cell 39 in clip section
Enter the environment you are using to run the notebook
Colab
Describe your issue
get_image_features and get_text_features used to return a plain torch.FloatTensor, but now they output a BaseModelOutputWithPooling. We cannot use .norm with this object, leading to an error in this line:
image_features /= image_features.norm(dim=1, keepdim=True)
with the error being:
AttributeError: 'BaseModelOutputWithPooling' object has no attribute 'norm'
If you found a workaround, describe it here
I have found a workaround after taking a look at different discussions in huggingface
output = self.clip_model.get_image_features(**inputs)
if not isinstance(output, torch.Tensor):
output = output.pooler_output
adding the following line fixes the issue
image_features = image_features.pooler_output