code: def scaled_dot_product_attention(
      q,
      k,
      v,
      scale: float,
      /,
      *,
      mask=None,
      out=None,
  ):
      if isinstance(mask, torch.Tensor):
          mask = torch.where(mask == 0, -torch.inf, 0)
      return xops.memory_efficient_attention(
          q, k, v, scale=scale, attn_bias=mask
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: scaled_dot_product_attention() and returns: xops