jax.lax.pmax

jax.lax.pmax(x, axis_name, *, axis_index_groups=None)

Compute an all-reduce max on x over the pmapped axis axis_name.

If x is a pytree then the result is equivalent to mapping this function to each leaf in the tree.

Parameters:

• x – array(s) with a mapped axis named axis_name.

• axis_name – hashable Python object used to name a pmapped axis (see the jax.pmap() documentation for more details).

• axis_index_groups – optional list of lists containing axis indices (e.g. for an axis of size 4, [[0, 1], [2, 3]] would perform pmaxes over the first two and last two replicas). Groups must cover all axis indices exactly once, and on TPUs all groups must be the same size.

Returns:

Array(s) with the same shape as x representing the result of an all-reduce max along the axis axis_name.