tf.contrib.distributions.WishartCholesky.prob(value, name='prob') Probability density/mass function (depending on is_continuous)

tf.contrib.distributions.Gamma.pdf(value, name='pdf') Probability density function. Args:

tf.contrib.distributions.ExponentialWithSoftplusLam.batch_shape(name='batch_shape') Shape of a single sample from a single event

tf.contrib.distributions.Exponential.get_event_shape() Shape of a single sample from a single batch as a TensorShape

tf.contrib.distributions.LaplaceWithSoftplusScale.batch_shape(name='batch_shape') Shape of a single sample from a single event

tf.contrib.distributions.Beta.get_batch_shape() Shape of a single sample from a single event index as a TensorShape

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.std(name='std') Standard deviation.

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.__init__(alpha, beta, validate_args=False, allow_nan_stats=True, name='InverseGammaWithSoftplusAlphaBeta')

tf.contrib.distributions.InverseGamma.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified shape

tf.contrib.distributions.Laplace.log_cdf(value, name='log_cdf') Log cumulative distribution function. Given