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tfp.experimental.substrates.numpy.math.log_sub_exp

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

tfp.experimental.substrates.numpy.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).