tfp.math.log_sub_exp

Compute log(exp(max(x, y)) - exp(min(x, y))) in a numerically stable way.

tfp.math.log_sub_exp(
    x, y, return_sign=False, name=None
)

Use return_sign=True unless x >= y, since we can't represent a negative in log-space.

Args
x	Float Tensor broadcastable with y.
y	Float Tensor broadcastable with x.
return_sign	Whether or not to return the second output value sign. If it is known that x >= y, this is unnecessary.
name	Python str name prefixed to Ops created by this function. Default value: None (i.e., 'log_sub_exp').

Returns
logsubexp	Float Tensor of log(exp(max(x, y)) - exp(min(x, y))).
sign	Float Tensor +/-1 indicating the sign of exp(x) - exp(y).