tfp.experimental.mcmc.WeightedParticles Stay organized with collections Save and categorize content based on your preferences.
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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