|
|
|
dataset = dict( |
|
type="VideoTextDataset", |
|
data_path=None, |
|
num_frames=1, |
|
frame_interval=1, |
|
image_size=(256, 256), |
|
transform_name="center", |
|
) |
|
|
|
|
|
num_workers = 4 |
|
dtype = "bf16" |
|
grad_checkpoint = False |
|
plugin = "zero2" |
|
sp_size = 1 |
|
|
|
|
|
model = dict( |
|
type="DiT-XL/2", |
|
no_temporal_pos_emb=True, |
|
enable_flashattn=True, |
|
enable_layernorm_kernel=True, |
|
) |
|
vae = dict( |
|
type="VideoAutoencoderKL", |
|
from_pretrained="stabilityai/sd-vae-ft-ema", |
|
) |
|
text_encoder = dict( |
|
type="clip", |
|
from_pretrained="openai/clip-vit-base-patch32", |
|
model_max_length=77, |
|
) |
|
scheduler = dict( |
|
type="iddpm", |
|
timestep_respacing="", |
|
) |
|
|
|
|
|
seed = 42 |
|
outputs = "outputs" |
|
wandb = False |
|
|
|
epochs = 1000 |
|
log_every = 10 |
|
ckpt_every = 1000 |
|
load = None |
|
|
|
batch_size = 128 |
|
lr = 1e-4 |
|
grad_clip = 1.0 |
|
|