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Adding a .cuda() in the return statement in categorical_accuracy fixed it for me:
def categorical_accuracy(preds, y, tag_pad_idx):
"""
Returns accuracy per batch, i.e. if you get 8/10 right, this returns 0.8, NOT 8
"""
max_preds = preds.argmax(dim = 1, keepdim = True) # get the index of the max probability
non_pad_elements = (y != tag_pad_idx).nonzero()
correct = max_preds[non_pad_elements].squeeze(1).eq(y[non_pad_elements])
return correct.sum() / torch.FloatTensor([y[non_pad_elements].shape[0]]).cuda()
Hi Ben..fanstactic repo.. quick one while running the same code - BiLSTM for PoS Tagging , I am getting the error in google colab :
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!
Please suggest
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