|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
dataset = dict( |
|
type="VideoTextDataset", |
|
data_path=None, |
|
num_frames=1, |
|
frame_interval=1, |
|
image_size=(256, 256), |
|
transform_name="center", |
|
) |
|
bucket_config = { |
|
"256": {1: (1.0, 256)}, |
|
"512": {1: (1.0, 80)}, |
|
"480p": {1: (1.0, 52)}, |
|
"1024": {1: (1.0, 20)}, |
|
"1080p": {1: (1.0, 8)}, |
|
} |
|
|
|
|
|
num_workers = 16 |
|
dtype = "bf16" |
|
grad_checkpoint = True |
|
plugin = "zero2" |
|
sp_size = 1 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
model = dict( |
|
type="PixArt-XL/2", |
|
space_scale=1.0, |
|
time_scale=1.0, |
|
no_temporal_pos_emb=True, |
|
from_pretrained="PixArt-XL-2-512x512.pth", |
|
enable_flash_attn=True, |
|
enable_layernorm_kernel=True, |
|
) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
vae = dict( |
|
type="VideoAutoencoderKL", |
|
from_pretrained="stabilityai/sd-vae-ft-ema", |
|
micro_batch_size=4, |
|
) |
|
text_encoder = dict( |
|
type="t5", |
|
from_pretrained="DeepFloyd/t5-v1_1-xxl", |
|
model_max_length=200, |
|
shardformer=True, |
|
) |
|
scheduler = dict( |
|
type="rflow", |
|
|
|
) |
|
|
|
|
|
seed = 42 |
|
outputs = "outputs" |
|
wandb = False |
|
|
|
epochs = 10 |
|
log_every = 10 |
|
ckpt_every = 500 |
|
load = None |
|
|
|
batch_size = 100 |
|
lr = 2e-5 |
|
grad_clip = 1.0 |
|
|