Hello @feizc ,
Thanks for the great work! I train the DiS-S/2 model for 200K steps using train.py and sample using unconditional DDPM for 250 time steps to generate 10K samples. Then I got the FID-10K=16.446, which is higher than the result in figure 2.
I follow the hyperparameters unchanged in train.py. For sampling, I follow the DiT Code and modify the sample_ddp.py and sample_ddp.sh which can be found in the sample_ddp.zip file. For FID computation, I pass both the reference cifar10-train folder and generated sample folder to test.py.
I wonder how to reproduce the results of unconditional CIFAR10 generation. Can you please help me with that? Really appreciate it.
Hello @feizc ,
Thanks for the great work! I train the DiS-S/2 model for 200K steps using train.py and sample using unconditional DDPM for 250 time steps to generate 10K samples. Then I got the FID-10K=16.446, which is higher than the result in figure 2.
I follow the hyperparameters unchanged in train.py. For sampling, I follow the DiT Code and modify the sample_ddp.py and sample_ddp.sh which can be found in the sample_ddp.zip file. For FID computation, I pass both the reference cifar10-train folder and generated sample folder to test.py.
I wonder how to reproduce the results of unconditional CIFAR10 generation. Can you please help me with that? Really appreciate it.