tf.contrib.distributions.StudentT.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

virtual Status tensorflow::WritableFile::Flush()=0

tf.contrib.framework.arg_scoped_arguments(func) Returns the list kwargs that arg_scope can set for a func. Args: func: function which has been decorated with @add_arg_scope. Returns: a list of kwargs names.

class tf.contrib.learn.monitors.CheckpointSaver Saves checkpoints every N steps.

tf.contrib.distributions.Binomial.n Number of trials.

tf.contrib.distributions.Categorical.log_prob(value, name='log_prob') Log probability density/mass function (depending on is_continuous). Args: value: float or double Tensor. name: The name to give this op. Returns: log_prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

tf.contrib.metrics.streaming_mean_relative_error(predictions, labels, normalizer, weights=None, metrics_collections=None, updates_collections=None, name=None) Computes the mean relative error by normalizing with the given values. The streaming_mean_relative_error function creates two local variables, total and count that are used to compute the mean relative absolute error. This average is weighted by weights, and it is ultimately returned as mean_relative_error: an idempotent operation that s

class tf.contrib.distributions.Dirichlet Dirichlet distribution. This distribution is parameterized by a vector alpha of concentration parameters for k classes.

tf.contrib.bayesflow.stochastic_tensor.TransformedDistributionTensor.distribution

tf.test.is_built_with_cuda() Returns whether TensorFlow was built with CUDA (GPU) support.