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The Arithmetic-Geometric Csiszar-function in log-space.

A Csiszar-function is a member of,

F = { f:R_+ to R : f convex }.

When self_normalized = True the Arithmetic-Geometric Csiszar-function is:

f(u) = (1 + u) log( (1 + u) / sqrt(u) ) - (1 + u) log(2)

When self_normalized = False the (1 + u) log(2) term is omitted.

Observe that as an f-Divergence, this Csiszar-function implies:

D_f[p, q] = KL[m, p] + KL[m, q]
m(x) = 0.5 p(x) + 0.5 q(x)

In a sense, this divergence is the "reverse" of the Jensen-Shannon f-Divergence.

This Csiszar-function induces a symmetric f-Divergence, i.e., D_f[p, q] = D_f[q, p].


  • logu: float-like Tensor representing log(u) from above.
  • self_normalized: Python bool indicating whether f'(u=1)=0. When f'(u=1)=0 the implied Csiszar f-Divergence remains non-negative even when p, q are unnormalized measures.
  • name: Python str name prefixed to Ops created by this function.


  • arithmetic_geometric_of_u: float-like Tensor of the Csiszar-function evaluated at u = exp(logu).