Internal state of GradientBasedTrajectoryLengthAdaptation.
tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptationResults(
inner_results, max_trajectory_length, step, adaptation_rate, jitter_amount,
averaged_sq_grad, averaged_max_trajectory_length, criterion, seed
)
Attributes |
inner_results
|
Results of the inner kernel.
|
max_trajectory_length
|
Floating point scalar Tensor . Maximum HMC
trajectory length.
|
step
|
Int32 scalar Tensor . The number of steps this kernel has taken.
Increases by 1 for every call to one_step .
|
adaptation_rate
|
Floating point scalar Tensor . How rapidly to adapt the
trajectory length.
|
jitter_amount
|
Floating point scalar Tensor . How much to jitter the
trajectory on the next step. The trajectory length is sampled from [(1 -
jitter_amount) * max_trajectory_length, max_trajectory_length] .
|
averaged_sq_grad
|
Floating point scalar Tensor . Moving average of squared
criterion gradients.
|
averaged_max_trajectory_length
|
Floating point scalar Tensor . Moving
average of the maximum of trajectory length. This is used after the burnin
period.
|
criterion
|
Floating point Tensor with shape [C0, ..., Cb] with b > 0 .
The value of the criterion returned by the criterion_fn corresponding to
each Markov chain.
|
seed
|
Int32 Tensor with shape [2] . The random seed used by the kernel in
the previous step.
|