tensorflow_privacy/privacy/analysis/rdp_accountant.py [64:88]:
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  if logy == -np.inf:  # subtracting 0
    return logx
  if logx == logy:
    return -np.inf  # 0 is represented as -np.inf in the log space.

  try:
    # Use exp(x) - exp(y) = (exp(x - y) - 1) * exp(y).
    return math.log(math.expm1(logx - logy)) + logy  # expm1(x) = exp(x) - 1
  except OverflowError:
    return logx


def _log_sub_sign(logx, logy):
  """Returns log(exp(logx)-exp(logy)) and its sign."""
  if logx > logy:
    s = True
    mag = logx + np.log(1 - np.exp(logy - logx))
  elif logx < logy:
    s = False
    mag = logy + np.log(1 - np.exp(logx - logy))
  else:
    s = True
    mag = -np.inf

  return s, mag
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tensorflow_privacy/privacy/analysis/rdp_privacy_accountant.py [42:66]:
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  if logy == -np.inf:  # subtracting 0
    return logx
  if logx == logy:
    return -np.inf  # 0 is represented as -np.inf in the log space.

  try:
    # Use exp(x) - exp(y) = (exp(x - y) - 1) * exp(y).
    return math.log(math.expm1(logx - logy)) + logy  # expm1(x) = exp(x) - 1
  except OverflowError:
    return logx


def _log_sub_sign(logx, logy):
  """Returns log(exp(logx)-exp(logy)) and its sign."""
  if logx > logy:
    s = True
    mag = logx + np.log(1 - np.exp(logy - logx))
  elif logx < logy:
    s = False
    mag = logy + np.log(1 - np.exp(logx - logy))
  else:
    s = True
    mag = -np.inf

  return s, mag
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