code: def _static_check_for_broadcastable_batch_shape(operators):
      """ValueError if operators determined to have non-broadcastable shapes."""
      if len(operators) < 2:
          return
  
      # This will fail if they cannot be broadcast together.
      batch_shape = operators[0].batch_shape
      for op in operators[1:]:
          batch_shape = array_ops.broadcast_static_shape(
              batch_shape, op.batch_shape
          )
  
imports: import abc
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops.linalg import linear_operator
  from tensorflow.python.ops.linalg import linear_operator_diag
  from tensorflow.python.ops.linalg import linear_operator_full_matrix
  from tensorflow.python.ops.linalg import linear_operator_identity
  from tensorflow.python.ops.linalg import linear_operator_lower_triangular
label_desc: Use image node_id 5 for calling a global function with example usage: _static_check_for_broadcastable_batch_shape(operators) without return types