tensorflow_probability/python/mcmc/internal/util.py
def make_innermost_getter(getter):
  """Wraps a getter so it applies to the inner-most results in `kernel_results`.

  The wrapped getter unwraps `kernel_results` and returns the return value of
  `getter` called with the first results without an `inner_results` attribute.

  Args:
    getter: A callable that takes Kernel results and returns some value.

  Returns:
    new_getter: A wrapped `getter`.
  """

  @functools.wraps(getter)
  def _new_getter(kernel_results, *args, **kwargs):
    """Wrapped getter."""
    results_stack = []
    while hasattr(kernel_results, 'inner_results'):
      results_stack.append(kernel_results)
      kernel_results = kernel_results.inner_results

    return getter(kernel_results, *args, **kwargs)

  return _new_getter
def make_innermost_getter(getter):
  @functools.wraps(getter)
  def _new_getter(kernel_results, *args, **kwargs):
    """Wrapped getter."""
    results_stack = []
    while hasattr(kernel_results, 'inner_results'):
      results_stack.append(kernel_results)
      kernel_results = kernel_results.inner_results

    return getter(kernel_results, *args, **kwargs)

  return _new_getter
def make_innermost_getter ( getter ) : @ functools . wraps ( getter ) def _new_getter ( kernel_results , * args , * * kwargs ) : """Wrapped getter.""" results_stack = [ ] while hasattr ( kernel_results , 'inner_results' ) : results_stack . append ( kernel_results ) kernel_results = kernel_results . inner_results return getter ( kernel_results , * args , * * kwargs ) return _new_getter
Wraps a getter so it applies to the inner-most results in `kernel_results`.

  The wrapped getter unwraps `kernel_results` and returns the return value of
  `getter` called with the first results without an `inner_results` attribute.

  Args:
    getter: A callable that takes Kernel results and returns some value.

  Returns:
    new_getter: A wrapped `getter`.
Wraps a getter so it applies to the inner - most results in kernel_results .