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# Define dataset
dataset = dict(
type="VideoTextDataset",
data_path=None,
num_frames=1,
frame_interval=1,
image_size=(256, 256),
transform_name="center",
)
# Define acceleration
num_workers = 4
dtype = "bf16"
grad_checkpoint = False
plugin = "zero2"
sp_size = 1
# Define model
model = dict(
type="DiT-XL/2",
no_temporal_pos_emb=True,
enable_flash_attn=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="",
)
# Others
seed = 42
outputs = "outputs"
wandb = False
epochs = 1000
log_every = 10
ckpt_every = 1000
load = None
batch_size = 128
lr = 1e-4 # according to DiT repo
grad_clip = 1.0
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