code: def forward(
      self,
      x_spatial: torch.Tensor,
      x_temporal: torch.Tensor,
      image_only_indicator: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      alpha = self.get_alpha(image_only_indicator)
      x = (
          alpha.to(x_spatial.dtype) * x_spatial
          + (1.0 - alpha).to(x_spatial.dtype) * x_temporal
      )
      return x
  
imports: import math
  from typing import Optional
  import torch
  import torch.nn
  from einops import rearrange, repeat
label_desc: Use image node_id 3 for calling the AlphaBlender obj's underlying member method code with example usage: obj.forward(x_spatial, x_temporal, image_only_indicator) and returns: x