updates
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@ -355,6 +355,11 @@ def compute_loss(p, targets, model): # predictions, targets, model
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lcls += BCEcls(ps[:, 5:], t) # BCE
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# lcls += CE(ps[:, 5:], tcls[i]) # CE
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# Instance-class weighting (use with reduction='none')
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# nt = t.sum(0) + 1 # number of targets per class
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# lcls += (BCEcls(ps[:, 5:], t) / nt).mean() * nt.mean() # v1
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# lcls += (BCEcls(ps[:, 5:], t) / nt[tcls[i]].view(-1,1)).mean() * nt.mean() # v2
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# Append targets to text file
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# with open('targets.txt', 'a') as file:
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# [file.write('%11.5g ' * 4 % tuple(x) + '\n') for x in torch.cat((txy[i], twh[i]), 1)]
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