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

tf.contrib.learn.monitors.StepCounter.epoch_end(epoch) End epoch. Args:

Status tensorflow::Env::RenameFile(const string &src, const string &target) Renames file src to target. If target already

tf.contrib.distributions.Beta.std(name='std') Standard deviation.

tf.contrib.learn.monitors.RunHookAdapterForMonitors.begin()

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

tf.contrib.graph_editor.SubGraphView.__init__(inside_ops=(), passthrough_ts=()) Create a subgraph containing the given ops and

tf.contrib.bayesflow.stochastic_tensor.DirichletMultinomialTensor.distribution

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

tf.minimum(x, y, name=None) Returns the min of x and y (i.e. x < y ? x : y) element-wise. NOTE: