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

tf.contrib.distributions.Multinomial.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes

tf.contrib.distributions.WishartFull.is_reparameterized

tf.contrib.distributions.Uniform.mean(name='mean') Mean.

tf.contrib.learn.monitors.LoggingTrainable.every_n_step_end(step, outputs)

tf.contrib.losses.cosine_distance(predictions, targets, dim, weight=1.0, scope=None) Adds a cosine-distance loss to the training

tf.contrib.learn.monitors.ValidationMonitor.every_n_step_begin(step) Callback before every n'th step begins.

class tf.contrib.learn.monitors.CaptureVariable Captures a variable's values into a collection. This

tf.imag(input, name=None) Returns the imaginary part of a complex number. Given a tensor input

tf.contrib.bayesflow.stochastic_tensor.BetaTensor.mean(name='mean')