is it possible to fine tune?

[juanluisrosaramos]

is it possible to fine tune?

[LLLPS666]

hello, have you solved this promble?
I can ues it to fine tune. But the model would be worse after training.
My training config is

python scripts/train.py
--dataset_type my_data_encode
--exp_dir my_model/mye4e
--use_w_pool
--w_discriminator_lambda 0.1
--progressive_start 20000
--id_lambda 0.5
--val_interval 10000
--max_steps 200
--stylegan_size 512
--stylegan_weights pretrained_models/stylegan2-ffhq-config-f.pt
--workers 8
--batch_size 16
--test_batch_size 4
--test_workers 4
--checkpoint_path pretrained_models/e4e_ffhq_encode.pt

[omertov]

Hi @juanluisrosaramos,
Sorry for the long response time,

In case it is still relevant, it seems like the file_path you provide for the stylegan_weights leads to a non-existing file, perhaps providing the absolute path to the weights file would help.
Also, just making sure that the StyleGAN checkpoint is compatible with rosinality's stylegan2-pytorch implementation, and not the nvidia's pytorch implementation. Last, I believe that the resume_training_from_ckpt would not yield the desired effect (there is no training information stored in the checkpoints I provided if thats what stored in pretrained_models/e4e_ffhq_encode.pt), you could use the --checkpoint_path flag to initialize the encoder from the pretrained weights.

As for @LLLPS666 's question - Is the error caused by the wrong stylegan_size specified? (512 instead of 1024)?

Best,
Omer