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just stated in your more recent work: https://arxiv.org/pdf/1911.03903.pdf, how you break ties when doing evaluation is important. And I wonder what tie handling method do you use in this work. It seems like TOP for me because of this line ranks = 1 + torch.argsort(torch.argsort(pred, dim=1, descending=True), dim=1, descending=False)[b_range, obj] But I am not 100% sure. Please correct me if I misunderstood your code!
The text was updated successfully, but these errors were encountered:
Hi,
just stated in your more recent work: https://arxiv.org/pdf/1911.03903.pdf, how you break ties when doing evaluation is important. And I wonder what tie handling method do you use in this work. It seems like TOP for me because of this line
ranks = 1 + torch.argsort(torch.argsort(pred, dim=1, descending=True), dim=1, descending=False)[b_range, obj]
But I am not 100% sure. Please correct me if I misunderstood your code!The text was updated successfully, but these errors were encountered: