int tensorflow::PartialTensorShape::dims() const Return the number of dimensions in the tensor. If the number of dimensions is unknown, return -1.

tf.contrib.distributions.Poisson.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.bayesflow.stochastic_tensor.StochasticTensor.input_dict

tf.contrib.learn.monitors.ExportMonitor.every_n_post_step(step, session) Callback after a step is finished or end() is called. Args: step: int, the current value of the global step. session: Session object.

tf.contrib.bayesflow.stochastic_tensor.WishartCholeskyTensor.dtype

tf.contrib.distributions.Chi2WithAbsDf.df

tf.contrib.distributions.Normal.log_pmf(value, name='log_pmf') Log probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: log_pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.distributions.WishartCholesky.sample_n(n, seed=None, name='sample_n') Generate n samples. Args: n: Scalar Tensor of type int32 or int64, the number of observations to sample. seed: Python integer seed for RNG name: name to give to the op. Returns: samples: a Tensor with a prepended dimension (n,). Raises: TypeError: if n is not an integer type.

tf.Session.reset(target, containers=None, config=None) Resets resource containers on target, and close all connected sessions. A resource container is distributed across all workers in the same cluster as target. When a resource container on target is reset, resources associated with that container will be cleared. In particular, all Variables in the container will become undefined: they lose their values and shapes. NOTE: (i) reset() is currently only implemented for distributed sessions. (ii

class tf.contrib.bayesflow.stochastic_tensor.GammaTensor GammaTensor is a StochasticTensor backed by the distribution Gamma.