TopK tensor, weight, 2 loss

[ericyq]

TopK = TopK_ALL[:, :K] local_embeddings, weight, local_patch_entropy = backbone(img_fft) double loss: torch.Tensor = module_partial_fc(local_embeddings, local_labels, opt, local_patch_entropy)

above TopK tensor, weight，all not to used. 2 loss also was not used in combination.

[DanJun6737]

Hi @ericyq ~

In fact, we implemente the weighting of the ArcFace loss function in the partial_fc_exp.py file, as the backward propagation of the ArcFace loss is defined in this file. Please refer to "class PartialFCAdamW".

[ericyq]

160th line, in train.py loss: torch.Tensor = module_partial_fc(local_embeddings, local_labels, opt, local_patch_entropy) here loss, isn't it not useful?

in addition, TopK tensor, is it not to used yet?

[DanJun6737]

Actually, we use the loss function on the 190th line in train.py to optimize the model. We utilize TopK factors to guide the generalization of new samples (lines 158-191 in train.py).