tf.contrib.distributions.QuantizedDistribution.log_prob()

tf.contrib.distributions.QuantizedDistribution.log_prob(value, name='log_prob')

Log probability density/mass function (depending on is_continuous).

Additional documentation from QuantizedDistribution:

For whole numbers y,

P[Y = y] := P[X <= lower_cutoff],  if y == lower_cutoff,
         := P[X > upper_cutoff - 1],  y == upper_cutoff,
         := 0, if j < lower_cutoff or y > upper_cutoff,
         := P[y - 1 < X <= y],  all other y.

The base distribution's log_cdf method must be defined on y - 1. If the base distribution has a log_survival_function method results will be more accurate for large values of y, and in this case the log_survival_function must also be defined on y - 1.

Args:

• value: float or double Tensor.
• name: The name to give this op.

Returns:

• log_prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.