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num_frames = 360
frame_interval = 1
image_size = (512, 512)
# Define dataset
root = None
data_path = "CSV_PATH"
use_image_transform = False
num_workers = 4
# Define acceleration
dtype = "bf16"
grad_checkpoint = True
plugin = "zero2-seq"
sp_size = 2
# Define model
model = dict(
type="STDiT-XL/2",
space_scale=1.0,
time_scale=2 / 3,
from_pretrained=None,
enable_flashattn=True,
enable_layernorm_kernel=True,
enable_sequence_parallelism=True, # enable sq here
)
vae = dict(
type="VideoAutoencoderKL",
from_pretrained="stabilityai/sd-vae-ft-ema",
micro_batch_size=128,
)
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 = 250
load = None
batch_size = 1
lr = 2e-5
grad_clip = 1.0
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