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the code is:
log_p = torch.log_softmax(pred_score, dim=1).reshape(-1, n_class)
where "pred_score" is a (n_batch, n_class, n_frame) tensor. then, doing log_softmax on it and reshape it in (-1,n_class). However, function "reshape" default in "Row first" mode, and we need "Col frist" mode here. the right code is:
log_p = torch.log_softmax(pred_score, dim=1).permute(0,2,1).reshape(-1, n_class)
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