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 _parameter_properties(cls, dtype):
      return dict()
  
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 2 for calling the MatrixInverseTriL obj's underlying member method code with example usage: obj._parameter_properties(cls, dtype) and returns: dict