[[subsets]]
caption_extension = ".txt"
image_dir = "D:/datasets/reg2"
name = "reg2"
num_repeats = 1
random_crop_padding_percent = 0.06

[[subsets]]
caption_extension = ".txt"
image_dir = "Y:/stable-diffusion/datasets/Artoria tiny"
keep_tokens = 1
name = "ishiri small"
num_repeats = 1
random_crop_padding_percent = 0.06

[[subsets]]
caption_extension = ".txt"
image_dir = "D:/datasets/reg"
name = "reg"
num_repeats = 1
random_crop_padding_percent = 0.06

[[subsets]]
caption_extension = ".txt"
image_dir = "D:/datasets/mix"
name = "mix"
num_repeats = 1
random_crop_padding_percent = 0.06

[[subsets]]
caption_extension = ".txt"
image_dir = "D:/datasets/vpred conversion"
name = "Vpred set"
num_repeats = 1
random_crop_padding_percent = 0.06

[train_mode]
train_mode = "lora"

[general_args.args]
persistent_data_loader_workers = true
pretrained_model_name_or_path = "C:/Users/norwa/Downloads/illustriousXL20_v20.safetensors"
debiased_estimation_loss = true
gradient_checkpointing = true
seed = 8602366.0
max_data_loader_n_workers = 4
max_token_length = 225
prior_loss_weight = 1.0
xformers = true
max_train_epochs = 50
cache_latents = true
cache_latents_to_disk = true
mixed_precision = "no"
v_parameterization = true
sdxl = true
gradient_accumulation_steps = 4
training_comment = "debiased estimation with sqrt(snr_t) / (snr_t+1) for vpred      fp32 run with some fp64 loss  added noise offset of 0.001      last testrun probably... if everything works out that is..."

[general_args.dataset_args]
resolution = 256
batch_size = 64

[network_args.args]
network_dim = 64
network_alpha = 128.0
min_timestep = 0
max_timestep = 1000
network_train_unet_only = true
cache_text_encoder_outputs = true
cache_text_encoder_outputs_to_disk = true

[optimizer_args.args]
lr_scheduler = "constant_with_warmup"
loss_type = "l2"
learning_rate = 4e-5
warmup_ratio = 0.02
max_grad_norm = 0.1
zero_terminal_snr = true
optimizer_type = "AdamW"

[saving_args.args]
save_model_as = "safetensors"
save_every_n_epochs = 1
save_toml = true
save_precision = "bf16"
output_name = "Illustrious-v2-256res-final-no-laplace-test-noffs001-fp32"
output_dir = "Y:/stable-diffusion/lora/derrian_distro/models/Illustrious-v2-256res-final-no-laplace-test-noffs001-fp32"
save_toml_location = "Y:/stable-diffusion/lora/derrian_distro/models/Illustrious-v2-256res-final-no-laplace-test-noffs001-fp32"

[noise_args.args]
noise_offset = 0.001

[logging_args.args]
log_prefix_mode = "disabled"
run_name_mode = "default"
log_with = "tensorboard"
logging_dir = "Y:/stable-diffusion/lora/derrian_distro/models/Illustrious-v2-256res-final-no-laplace-test-noffs001-fp32"

[edm_loss_args.args]
edm2_loss_weighting = false

[extra_args.args]
pin_data_loader_memory = "True"
disable_cuda_reduced_precision_operations = "True"

[bucket_args.dataset_args]
enable_bucket = true
bucket_reso_steps = 64
max_bucket_reso = 320
min_bucket_reso = 192

[network_args.args.network_args]
conv_dim = 64
conv_alpha = 128.0
algo = "locon"
dora_wd = true
train_norm = true

[optimizer_args.args.optimizer_args]
weight_decay = "0.042"
betas = "0.9,0.99"