tf.contrib.distributions.TransformedDistribution.get_event_shape()

tf.contrib.distributions.TransformedDistribution.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

tf.contrib.distributions.TransformedDistribution.get_batch_shape()

tf.contrib.distributions.TransformedDistribution.get_batch_shape() Shape of a single sample from a single event index as a TensorShape. Same meaning as batch_shape. May be only partially defined. Returns: batch_shape: TensorShape, possibly unknown.

tf.contrib.distributions.TransformedDistribution.event_shape()

tf.contrib.distributions.TransformedDistribution.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor. Args: name: name to give to the op Returns: event_shape: Tensor.

tf.contrib.distributions.TransformedDistribution.dtype

tf.contrib.distributions.TransformedDistribution.dtype The DType of Tensors handled by this Distribution.

tf.contrib.distributions.TransformedDistribution.entropy()

tf.contrib.distributions.TransformedDistribution.entropy(name='entropy') Shanon entropy in nats.

tf.contrib.distributions.TransformedDistribution.cdf()

tf.contrib.distributions.TransformedDistribution.cdf(value, name='cdf') Cumulative distribution function. Given random variable X, the cumulative distribution function cdf is: cdf(x) := P[X <= x] Args: value: float or double Tensor. name: The name to give this op. Returns: cdf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

tf.contrib.distributions.TransformedDistribution.batch_shape()

tf.contrib.distributions.TransformedDistribution.batch_shape(name='batch_shape') Shape of a single sample from a single event index as a 1-D Tensor. The product of the dimensions of the batch_shape is the number of independent distributions of this kind the instance represents. Args: name: name to give to the op Returns: batch_shape: Tensor.

tf.contrib.distributions.TransformedDistribution.allow_nan_stats

tf.contrib.distributions.TransformedDistribution.allow_nan_stats Python boolean describing behavior when a stat is undefined. Stats return +/- infinity when it makes sense. E.g., the variance of a Cauchy distribution is infinity. However, sometimes the statistic is undefined, e.g., if a distribution's pdf does not achieve a maximum within the support of the distribution, the mode is undefined. If the mean is undefined, then by definition the variance is undefined. E.g. the mean for Student's T

tf.contrib.distributions.TransformedDistribution.base_distribution

tf.contrib.distributions.TransformedDistribution.base_distribution Base distribution, p(x).

tf.contrib.distributions.TransformedDistribution

class tf.contrib.distributions.TransformedDistribution A Transformed Distribution. A Transformed Distribution models p(y) given a base distribution p(x), an invertible transform, y = f(x), and the determinant of the Jacobian of f(x). Shapes, type, and reparameterization are taken from the base distribution.