tfp.experimental.mcmc.WeightedParticles
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Particles with corresponding log weights.
tfp.experimental.mcmc.WeightedParticles(
particles, log_weights
)
This structure serves as the state for the SequentialMonteCarlo transition
kernel.
Elements |
|---|
particles
|
a (structure of) Tensor(s) each of shape
concat([[num_particles, b1, ..., bN], event_shape]), where event_shape
may differ across component Tensors.
|
log_weights
|
float Tensor of shape
[num_particles, b1, ..., bN] containing a log importance weight for
each particle, typically normalized so that
exp(reduce_logsumexp(log_weights, axis=0)) == 1.. These must be used in
conjunction with particles to compute expectations under the target
distribution.
|
In some contexts, particles may be stacked across multiple inference steps,
in which case all Tensor shapes will be prefixed by an additional dimension
of size num_steps.
Attributes |
|---|
particles
|
A namedtuple alias for field number 0
|
log_weights
|
A namedtuple alias for field number 1
|
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Last updated 2023-11-21 UTC.
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View source on GitHub