def make_fast_adapt_kernel(*, kind, proposal_kernel_kwargs, dual_averaging_kwargs): return dassa.DualAveragingStepSizeAdaptation( _make_base_kernel( kind=kind, proposal_kernel_kwargs=proposal_kernel_kwargs), **dual_averaging_kwargs)
def make_fast_adapt_kernel(*, target_log_prob_fn, initial_step_size, num_leapfrog_steps, num_adaptation_steps, target_accept_prob, momentum_distribution): return dassa.DualAveragingStepSizeAdaptation( _make_base_kernel(target_log_prob_fn=target_log_prob_fn, step_size=initial_step_size, num_leapfrog_steps=num_leapfrog_steps, momentum_distribution=momentum_distribution), shrinkage_target=initial_step_size, num_adaptation_steps=num_adaptation_steps, target_accept_prob=target_accept_prob)