tf.contrib.bayesflow.stochastic_tensor.Chi2WithAbsDfTensor.graph

tf.contrib.distributions.MultivariateNormalCholesky.is_continuous

tf.nn.rnn_cell.OutputProjectionWrapper.state_size

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

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.

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

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.MultivariateNormalDiagTensor MultivariateNormalDiagTensor is a StochasticTensor backed by the distribution MultivariateNormalDiag.

tf.TensorArray.size(name=None) Return the size of the TensorArray.

tf.contrib.bayesflow.stochastic_tensor.QuantizedDistributionTensor.loss(final_loss, name='Loss')