code: def batch_broadcast(a, x):
      """Broadcasts a over all dimensions of x, except the batch dimension,
      which must match."""
  
      if len(a.shape) != 1:
          a = a.squeeze()
          if len(a.shape) != 1:
              raise ValueError(
                  f"Don't know how to batch-broadcast tensor `a` "
                  f"with more than one effective dimension (shape {a.shape})"
              )
  
      if a.shape[0] != x.shape[0] and a.shape[0] != 1:
          raise ValueError(
              f"Don't know how to batch-broadcast shape {a.shape} over {x.shape} "
              "as the batch dimension is not matching"
          )
  
      out = a.view((x.shape[0], *(1 for _ in range(len(x.shape) - 1))))
      return out
  
imports: import abc
  import warnings
  import numpy
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: batch_broadcast(a, x) and returns: out