tf.contrib.distributions.Exponential.survival_function(value, name='survival_function') Survival function. Given

tf.contrib.bayesflow.stochastic_tensor.InverseGammaWithSoftplusAlphaBetaTensor.distribution

class tf.contrib.learn.monitors.EveryN Base class for monitors that execute callbacks every N steps. This

tf.contrib.learn.monitors.CaptureVariable.every_n_post_step(step, session) Callback after a step is finished or end()

tf.contrib.bayesflow.stochastic_tensor.GammaTensor.clone(name=None, **dist_args)

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.log_prob(value, name='log_prob') Log probability density/mass function

tf.image.per_image_whitening(image) Linearly scales image to have zero mean and unit norm. This

tf.nn.rnn_cell.BasicLSTMCell.__init__(num_units, forget_bias=1.0, input_size=None, state_is_tuple=True, activation=tanh) Initialize

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

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