Spaces:
Runtime error
Runtime error
| _base_ = ['../PixArt_xl2_internal.py'] | |
| data_root = 'data' | |
| image_list_json = ['data_info.json',] | |
| data = dict(type='InternalData', root='InternData', image_list_json=image_list_json, transform='default_train', load_vae_feat=True) | |
| image_size = 256 | |
| # model setting | |
| model = 'PixArt_XL_2' | |
| fp32_attention = True | |
| load_from = None | |
| vae_pretrained = "output/pretrained_models/sd-vae-ft-ema" | |
| # training setting | |
| eval_sampling_steps = 200 | |
| num_workers=10 | |
| train_batch_size = 176 # 32 # max 96 for PixArt-L/4 when grad_checkpoint | |
| num_epochs = 200 # 3 | |
| gradient_accumulation_steps = 1 | |
| grad_checkpointing = True | |
| gradient_clip = 0.01 | |
| optimizer = dict(type='AdamW', lr=2e-5, weight_decay=3e-2, eps=1e-10) | |
| lr_schedule_args = dict(num_warmup_steps=1000) | |
| log_interval = 20 | |
| save_model_epochs=5 | |
| work_dir = 'output/debug' | |