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num_frames = 16 | |
frame_interval = 3 | |
image_size = (256, 256) | |
# Define dataset | |
root = None | |
data_path = "CSV_PATH" | |
use_image_transform = False | |
num_workers = 4 | |
# Define acceleration | |
dtype = "bf16" | |
grad_checkpoint = False | |
plugin = "zero2" | |
sp_size = 1 | |
# Define model | |
model = dict( | |
type="PixArt-XL/2", | |
space_scale=0.5, | |
time_scale=1.0, | |
from_pretrained="PixArt-XL-2-512x512.pth", | |
enable_flashattn=True, | |
enable_layernorm_kernel=True, | |
) | |
vae = dict( | |
type="VideoAutoencoderKL", | |
from_pretrained="stabilityai/sd-vae-ft-ema", | |
) | |
text_encoder = dict( | |
type="t5", | |
from_pretrained="./pretrained_models/t5_ckpts", | |
model_max_length=120, | |
shardformer=True, | |
) | |
scheduler = dict( | |
type="iddpm", | |
timestep_respacing="", | |
) | |
# Others | |
seed = 42 | |
outputs = "outputs" | |
wandb = False | |
epochs = 1000 | |
log_every = 10 | |
ckpt_every = 1000 | |
load = None | |
batch_size = 8 | |
lr = 2e-5 | |
grad_clip = 1.0 | |