code: def __init__(
      self,
      *args,
      video_kernel_size: Union[int, list] = 3,
      alpha: float = 0.0,
      merge_strategy: str = "learned",
      time_mode: str = "conv-only",
      **kwargs,
  ):
      self.video_kernel_size = video_kernel_size
      self.alpha = alpha
      self.merge_strategy = merge_strategy
      self.time_mode = time_mode
      assert (
          self.time_mode in self.available_time_modes
      ), f"time_mode parameter has to be in {self.available_time_modes}"
      super().__init__(*args, **kwargs)
  
imports: from typing import Callable, Iterable, Union
  import torch
  from einops import rearrange, repeat
  from sgm.modules.diffusionmodules.model import XFORMERS_IS_AVAILABLE, AttnBlock, Decoder, MemoryEfficientAttnBlock, ResnetBlock
  from sgm.modules.diffusionmodules.openaimodel import ResBlock, timestep_embedding
  from sgm.modules.video_attention import VideoTransformerBlock
  from sgm.util import partialclass
label_desc: Use image node_id 1 to create a new VideoDecoder object from inherited base classes: Decoder with example: obj = VideoDecoder()