class tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor MultivariateNormalDiagTensor is a StochasticTensor backed by the distribution MultivariateNormalDiag.

tf.contrib.learn.monitors.GraphDump.begin(max_steps=None)

tf.contrib.learn.monitors.ExportMonitor.step_begin(step) Overrides BaseMonitor.step_begin. When overriding this method, you must call the super implementation. Args: step: int, the current value of the global step. Returns: A list, the result of every_n_step_begin, if that was called this step, or an empty list otherwise. Raises: ValueError: if called more than once during a step.

class tf.contrib.bayesflow.stochastic_tensor.DirichletMultinomialTensor DirichletMultinomialTensor is a StochasticTensor backed by the distribution DirichletMultinomial.

tf.contrib.distributions.NormalWithSoftplusSigma.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.WishartFull.variance(name='variance') Variance.

tf.contrib.util.make_ndarray(tensor) Create a numpy ndarray from a tensor. Create a numpy ndarray with the same shape and data as the tensor. Args: tensor: A TensorProto. Returns: A numpy array with the tensor contents. Raises: TypeError: if tensor has unsupported type.

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

bool tensorflow::PartialTensorShape::IsValid(const TensorShapeProto &proto) Returns true iff proto is a valid partial tensor shape.