code: def einsum(equation, *operands):
      """
      Log-sum-exp implementation of einsum.
      """
      if get_backend() != "jax":
          # NB: rename symbols to support NumPy, which allow only symbols a-z.
          symbols = sorted(set(equation) - set(",->"))
          rename = dict(zip(symbols, "abcdefghijklmnopqrstuvwxyz"))
          equation = "".join(rename.get(s, s) for s in equation)
  
      inputs, output = equation.split("->")
      if inputs == output:
          return operands[0][...]  # create a new object
      inputs = inputs.split(",")
  
      shifts = []
      exp_operands = []
      for dims, operand in zip(inputs, operands):
          shift = ops.detach(operand)
          for i, dim in enumerate(dims):
              if dim not in output:
                  shift = ops.amax(shift, i, keepdims=True)
          # avoid nan due to -inf - -inf
          shift = ops.clamp(shift, ops.finfo(shift).min, None)
          exp_operands.append(ops.exp(operand - shift))
  
          # permute shift to match output
          shift = shift.reshape(
              [
                  size
                  for size, dim in zip(operand.shape, dims)
                  if dim in output
              ]
          )
          if len(shift.shape) > 0:
              shift = shift.reshape(
                  (1,) * (len(output) - shift.ndim) + shift.shape
              )
              dims = [dim for dim in dims if dim in output]
              dims = [dim for dim in output if dim not in dims] + dims
              shift = ops.permute(
                  shift, [dims.index(dim) for dim in output]
              )
          shifts.append(shift)
  
      result = ops.log(ops.einsum(exp_operands, equation))
      return sum(shifts + [result])
  
label_desc: Use image node_id 1 for calling a global function with example usage: einsum(equation) and returns: sum, operands