code: def dropout_add(x, bias, residual, prob, training):
      # type: (Tensor, None, Tensor, float, bool) -> Tensor
      if bias is not None:
          raise ValueError(
              f"bias is expected to be None when using the bias_dropout function."
          )
      out = torch.nn.functional.dropout(x, p=prob, training=training)
      out = residual + out
      return out
  
imports: import torch
label_desc: Use image node_id 1 for calling a global function with example usage: dropout_add(x, bias, residual, prob, training) and returns: out