code: def _lu_solve_assertions(lower_upper, perm, rhs, validate_args):
      """Returns list of assertions related to `lu_solve` assumptions."""
      assertions = lu_reconstruct_assertions(
          lower_upper, perm, validate_args
      )
  
      message = "Input `rhs` must have at least 2 dimensions."
      if tensorshape_util.rank(rhs.shape) is not None:
          if tensorshape_util.rank(rhs.shape) < 2:
              raise ValueError(message)
      elif validate_args:
          assertions.append(
              assert_util.assert_rank_at_least(
                  rhs, rank=2, message=message
              )
          )
  
      message = "`lower_upper.shape[-1]` must equal `rhs.shape[-1]`."
      if (
          tf.compat.dimension_value(lower_upper.shape[-1]) is not None
          and tf.compat.dimension_value(rhs.shape[-2]) is not None
      ):
          if lower_upper.shape[-1] != rhs.shape[-2]:
              raise ValueError(message)
      elif validate_args:
          assertions.append(
              assert_util.assert_equal(
                  tf.shape(lower_upper)[-1],
                  tf.shape(rhs)[-2],
                  message=message,
              )
          )
  
      return assertions
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import custom_gradient
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.math import generic
label_desc: Use image node_id 11 for calling a global function with example usage: _lu_solve_assertions(lower_upper, perm, rhs, validate_args) and returns: assertions