Comments (3)
quick fix is to add
device = next(self.parameters()).device
tokens = tokens.to(device)
in the forward method e.g. here https://github.com/oxpig/CaLM/blob/main/calm/model.py#L107
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Hi @adrienchaton,
The quick fix you mention is likely correct — however, a better practice would be to instantiate the model in the CPU and then transfer it to the GPU (as well as the tokens). Here is some example code:
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = ProteinBertModel(args, alphabet)
model = model.to(device)
# ...
tokens = tokens.to(device)
logits = model(tokens)
Best wishes,
Carlos
from calm.
Thanks for your reply and sharing the code snippet.
This is indeed what I would do in my own codes (+ possibly already instantiating the tensor on GPU device for speed-up and best practice), but the usage you recommend in your readme for inference with pre-trained model isn't this.
I find unfortunate that the proposed usage doesn't allow using GPU, but the great work and right to ignore this are yours.
from calm.
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