Questions about Mask h (x)

[zhaoxueyi6]

Hello author，I have a question that I seem to have not found the position of the mask h in get_features to decompose the time series x into the informative part x *. Could you please let me know.I see that it seems that x has been directly enhanced to form ax. def get_features(self, x, training = True, n_epochs=-1, mask=None):

    embedding = self.augsharenet(x)   
    weight_h = self.factor_augnet(embedding)  
    weight_s = self.augmentation_projector(embedding)  

    
    mask_h = self._sample_graph(weight_h,training= training)  #输出（32，257，8）

    if self.hard_mask:
        hard_mask_h = (torch.sign(mask_h-0.5)+1)/2
        # print(hard_mask_h)

mask_h = (mask_h-hard_mask_h).detach()+hard_mask_h

        mask_h = (hard_mask_h - mask_h).detach()+mask_h
    ax = weight_s * mask_h * x  # augmented x'

    
    if torch.isnan(ax).any() or torch.isnan(x).any():
        exit(1)

    # note: I add mask
    out1 = self._net(x,mask)  # representation
    out2 = self._net(ax,mask)  # representation of augmented x'
    return x, ax, out1, out2, weight_h

[AslanDing]

The informative part is mask_h*x. It is part of " ax = weight_s * mask_h * x " Thanks.

[zhaoxueyi6]

I understand, thank you!！