Issue with patchcore anomaly score for large confidence scores

[bsl546]

Describe the bug When the confidence is very high for images treated by the patchcore model, the anomaly score can be nan. This is due to the formula: weights = 1 - (torch.max(torch.exp(confidence)) / torch.sum(torch.exp(confidence))) in anomaly_map.py, torch.exp() gives nan for values too large.

Expected behavior Two possible solutions:

• Either a threshold should be set on the tensors, like confidence[confidence>thres] = thres Possible values for thres are e.g., 50.0.

• Or, even cleaner, replace 1- (torch.max(torch.exp(confidence)) / torch.sum(torch.exp(confidence))) by 1-torch.max(torch.nn.Softmax()(confidence))