|
|
|
dataset = dict( |
|
type="VariableVideoTextDataset", |
|
transform_name="resize_crop", |
|
) |
|
bucket_config = { |
|
"144p": {1: (0.5, 48), 34: (1.0, 2), 51: (1.0, 4), 102: (1.0, 2), 204: (1.0, 1)}, |
|
|
|
"256": {1: (0.6, 20), 34: (0.5, 2), 51: (0.5, 1), 68: (0.5, 1), 136: (0.0, None)}, |
|
"240p": {1: (0.6, 20), 34: (0.5, 2), 51: (0.5, 1), 68: (0.5, 1), 136: (0.0, None)}, |
|
|
|
"360p": {1: (0.5, 8), 34: (0.2, 1), 102: (0.0, None)}, |
|
"512": {1: (0.5, 8), 34: (0.2, 1), 102: (0.0, None)}, |
|
|
|
"480p": {1: (0.2, 4), 17: (0.3, 1), 68: (0.0, None)}, |
|
|
|
"720p": {1: (0.1, 2)}, |
|
"1024": {1: (0.1, 2)}, |
|
|
|
"1080p": {1: (0.1, 1)}, |
|
} |
|
grad_checkpoint = False |
|
|
|
|
|
num_workers = 8 |
|
num_bucket_build_workers = 16 |
|
dtype = "bf16" |
|
plugin = "zero2" |
|
|
|
|
|
model = dict( |
|
type="STDiT3-XL/2", |
|
from_pretrained=None, |
|
qk_norm=True, |
|
enable_flash_attn=True, |
|
enable_layernorm_kernel=True, |
|
) |
|
vae = dict( |
|
type="OpenSoraVAE_V1_2", |
|
from_pretrained="pretrained_models/vae-pipeline", |
|
micro_frame_size=17, |
|
micro_batch_size=4, |
|
) |
|
text_encoder = dict( |
|
type="t5", |
|
from_pretrained="DeepFloyd/t5-v1_1-xxl", |
|
model_max_length=300, |
|
shardformer=True, |
|
local_files_only=True, |
|
) |
|
scheduler = dict( |
|
type="rflow", |
|
use_timestep_transform=True, |
|
sample_method="logit-normal", |
|
) |
|
|
|
|
|
mask_ratios = { |
|
"random": 0.2, |
|
"intepolate": 0.01, |
|
"quarter_random": 0.01, |
|
"quarter_head": 0.01, |
|
"quarter_tail": 0.01, |
|
"quarter_head_tail": 0.01, |
|
"image_random": 0.05, |
|
"image_head": 0.1, |
|
"image_tail": 0.05, |
|
"image_head_tail": 0.05, |
|
} |
|
|
|
|
|
seed = 42 |
|
outputs = "outputs" |
|
wandb = False |
|
epochs = 1000 |
|
log_every = 10 |
|
ckpt_every = 500 |
|
|
|
|
|
load = None |
|
grad_clip = 1.0 |
|
lr = 1e-4 |
|
ema_decay = 0.99 |
|
adam_eps = 1e-15 |
|
|