tfp.experimental.distribute.make_sharded_log_prob_parts

Constructs a log prob parts function that all-reduces over terms.

tfp.experimental.distribute.make_sharded_log_prob_parts(
    log_prob_parts_fn, is_sharded, axis_name=None
)

Given a log_prob_parts function, this function will return a new one that includes all-reduce sums over terms according to the is_sharded property. It will also add all-reduce sums for the gradient of sharded terms w.r.t. unsharded terms.

log_prob_parts_fn a callable that takes in a structured value and returns a structure of log densities for each of the terms, that when summed returns a locally correct log-density.
is_sharded a structure of boolean values that matches the input and output of log_prob_parts_fn. If a value in log_prob_parts_fn has a corresponding is_sharded value set to True, the returned function will add an all-reduce sum for its term in the log prob calculation. If it is False, the returned function will have an all-reduce sum over the gradient of sharded terms w.r.t. to the unsharded value.
axis_name a str used for the axis name in the JAX backend. Unused in the TensorFlow backend.

A new log prob parts function that can be run inside of strategy.