FLUX LoRA Training - Text Encoder active training indicated when it should be disabled with --network_train_unet_only

[Enyakk]

The log for my training shows:
INFO create LoRA network. base dim (rank): 128, alpha: 128 lora_flux.py:594
INFO neuron dropout: p=0.25, rank dropout: p=None, module dropout: p=None lora_flux.py:595
INFO split qkv for LoRA lora_flux.py:603
INFO train all blocks only lora_flux.py:605
INFO create LoRA for Text Encoder 1: lora_flux.py:741
INFO create LoRA for Text Encoder 1: 72 modules. lora_flux.py:744
INFO create LoRA for FLUX all blocks: 6 modules. lora_flux.py:765
INFO enable LoRA for U-Net: 6 modules lora_flux.py:916

That is despite using the option --network_train_unet_only both by commandline and in the config-toml: network_train_unet_only = true.
I use the following commandline:
accelerate launch --num_cpu_threads_per_process 1 flux_train_network.py --persistent_data_loader_workers --max_data_loader_n_workers 2 --highvram --network_train_unet_only --config_file %1
config_lora.zip

This option might be out of the ordinary:
network_args = [ "train_double_block_indices=none", "train_single_block_indices=7,20", "split_qkv=True",]

[Enyakk]

I have retested with a standard LoRA (training allblocks) and I get the same result of TE1 training being indicated in the log. I don't know if that's actually the case but it does seem that way to me. The size of the resulting .safetensor does indicate that it includes the additional TE1 modules though.

[kohya-ss]

INFO create LoRA for Text Encoder 1: lora_flux.py:741
INFO create LoRA for Text Encoder 1: 72 modules. lora_flux.py:744
INFO create LoRA for FLUX all blocks: 6 modules. lora_flux.py:765
INFO enable LoRA for U-Net: 6 modules lora_flux.py:916

This log indicates that several LoRA modules were created, but only six of them were trained as active modules.

Please run networks/check_lora_weights.py with python networks/check_lora_weights.py path/to/trained_lora.safetensors. It shows the keys in the safetensors, so uou can see which modules are included. If it contains modules for Text Encoders (keys start with lora_te), please report it. Otherwise only U-Net(DiT) is trained, and it's fine.