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from typing import Literal
from pydantic import BaseModel
from torch.cuda import is_available
class Args(BaseModel):
test_image_path: str
test_audio_path: str
test_hubert_path: str
result_path: str = "./outputs/"
stage1_checkpoint_path: str = "ckpts/stage1.ckpt"
stage2_checkpoint_path: str
control_flag: bool = True
pose_driven_path: str = "not_supported_in_this_mode"
image_size: int = 256
device: Literal["cuda", "cpu"] = "cuda" if is_available() else "cpu"
motion_dim: int = 20
decoder_layers: int = 2
class DefaultValues(BaseModel):
pose_yaw: float = 0.0
pose_pitch: float = 0.0
pose_roll: float = 0.0
face_location: float = 0.5
face_scale: float = 0.5
step_T: int = 50
seed: int = 0
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