tensorflow_probability/python/mcmc/hmc.py
def bootstrap_results(self, init_state):
    """Creates initial `previous_kernel_results` using a supplied `state`."""
    kernel_results = self._impl.bootstrap_results(init_state)
    if self.step_size_update_fn is not None:
      step_size_assign = self.step_size_update_fn(self.step_size, None)  # pylint: disable=not-callable
      kernel_results = kernel_results._replace(
          extra=HamiltonianMonteCarloExtraKernelResults(
              step_size_assign=step_size_assign))
    return kernel_results
def bootstrap_results(self, init_state):
    kernel_results = self._impl.bootstrap_results(init_state)
    if self.step_size_update_fn is not None:
      step_size_assign = self.step_size_update_fn(self.step_size, None)  # pylint: disable=not-callable
      kernel_results = kernel_results._replace(
          extra=HamiltonianMonteCarloExtraKernelResults(
              step_size_assign=step_size_assign))
    return kernel_results
def bootstrap_results ( self , init_state ) : kernel_results = self . _impl . bootstrap_results ( init_state ) if self . step_size_update_fn is not None : step_size_assign = self . step_size_update_fn ( self . step_size , None ) # pylint: disable=not-callable kernel_results = kernel_results . _replace ( extra = HamiltonianMonteCarloExtraKernelResults ( step_size_assign = step_size_assign ) ) return kernel_results
Creates initial `previous_kernel_results` using a supplied `state`.
Creates initial previous_kernel_results using a supplied state .