class_docstr: Computes `g(L) = inv(L)`, where `L` is a lower-triangular matrix.
  
  `L` must be nonsingular; equivalently, all diagonal entries of `L` must be
  nonzero.
  
  The input must have `rank >= 2`.  The input is treated as a batch of matrices
  with batch shape `input.shape[:-2]`, where each matrix has dimensions
  `input.shape[-2]` by `input.shape[-1]` (hence `input.shape[-2]` must equal
  `input.shape[-1]`).
  
  #### Examples
  
  ```python
  tfp.bijectors.MatrixInverseTriL().forward(x=[[1., 0], [2, 1]])
  # Result: [[1., 0], [-2, 1]], i.e., inv(x)
  
  tfp.bijectors.MatrixInverseTriL().inverse(y=[[1., 0], [-2, 1]])
  # Result: [[1., 0], [2, 1]], i.e., inv(y).
  ```
code: def _assertions(self, x):
      if not self.validate_args:
          return []
      shape = tf.shape(x)
      is_matrix = assert_util.assert_rank_at_least(
          x, 2, message="Input must have rank at least 2."
      )
      is_square = assert_util.assert_equal(
          shape[-2], shape[-1], message="Input must be a square matrix."
      )
      above_diagonal = tf.linalg.band_part(
          tf.linalg.set_diag(x, tf.zeros(shape[:-1], dtype=tf.float32)),
          0,
          -1,
      )
      is_lower_triangular = assert_util.assert_equal(
          above_diagonal,
          tf.zeros_like(above_diagonal),
          message="Input must be lower triangular.",
      )
      # A lower triangular matrix is nonsingular iff all its diagonal entries are
      # nonzero.
      diag_part = tf.linalg.diag_part(x)
      is_nonsingular = assert_util.assert_none_equal(
          diag_part,
          tf.zeros_like(diag_part),
          message="Input must have all diagonal entries nonzero.",
      )
      return [is_matrix, is_square, is_lower_triangular, is_nonsingular]
  
file_path: probability/tensorflow_probability/python/bijectors/matrix_inverse_tril.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
label_desc: Use image node_id 6 for calling the MatrixInverseTriL obj's underlying member method code with example usage: obj._assertions(x) and returns: list, list