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Hi, thank you for sharing the amazing and inspiring pruning work! We have a question related to the pruning code for LDM.We are confused why in the prune_ldm.py line 120 the sampled latent is further encoded with the encoder and then feed into the model for calculating the loss at time t. Shouldn't it just be the sampled latent without encoding? Thanks!
The text was updated successfully, but these errors were encountered:
Hello @JinyangMarkLiu, we used ImageNet images for pruning. I don't remember why this script generated samples for importance estimation. I guess I modified the original code for exploration. Let me check the code version.
Hi, thank you for sharing the amazing and inspiring pruning work! We have a question related to the pruning code for LDM.We are confused why in the prune_ldm.py line 120 the sampled latent is further encoded with the encoder and then feed into the model for calculating the loss at time t. Shouldn't it just be the sampled latent without encoding? Thanks!
The text was updated successfully, but these errors were encountered: