Spaces:
Runtime error
Runtime error
File size: 1,465 Bytes
eadd7b4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
_base_ = ['../PixArt_xl2_internal.py']
data_root = 'pixart-sigma-toy-dataset'
image_list_json = ['data_info.json']
data = dict(
type='InternalDataMSSigma', root='InternData', image_list_json=image_list_json, transform='default_train',
load_vae_feat=True, load_t5_feat=True,
)
image_size = 1024
# model setting
model = 'PixArtMS_XL_2' # model for multi-scale training
fp32_attention = False
load_from = None
resume_from = None
vae_pretrained = "output/pretrained_models/pixart_sigma_sdxlvae_T5_diffusers/vae" # sdxl vae
aspect_ratio_type = 'ASPECT_RATIO_1024'
multi_scale = True # if use multiscale dataset model training
pe_interpolation = 2.0
# training setting
num_workers = 4
train_batch_size = 12 # max 12 for PixArt-xL/2 when grad_checkpoint
num_epochs = 10 # 3
gradient_accumulation_steps = 1
grad_checkpointing = True
gradient_clip = 0.01
optimizer = dict(type='CAMEWrapper', lr=1e-5, weight_decay=0.0, betas=(0.9, 0.999, 0.9999), eps=(1e-30, 1e-16))
lr_schedule_args = dict(num_warmup_steps=100)
save_model_epochs = 10
save_model_steps = 1000
valid_num = 0 # take as valid aspect-ratio when sample number >= valid_num
log_interval = 10
eval_sampling_steps = 5
visualize = True
work_dir = 'output/debug'
# pixart-sigma
scale_factor = 0.13025
real_prompt_ratio = 0.5
model_max_length = 300
class_dropout_prob = 0.1
# LCM
loss_type = 'huber'
huber_c = 0.001
num_ddim_timesteps = 50
w_max = 15.0
w_min = 3.0
ema_decay = 0.95
cfg_scale = 4.5
|