tf.ReaderBase.reset(name=None) Restore a reader to its initial clean state. Args: name: A name for the operation (optional). Returns: The created Operation.

tf.contrib.learn.monitors.PrintTensor.begin(max_steps=None) Called at the beginning of training. When called, the default graph is the one we are executing. Args: max_steps: int, the maximum global step this training will run until. Raises: ValueError: if we've already begun a run.

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.is_continuous

tf.contrib.graph_editor.SubGraphView.output_index(t) Find the output index corresponding to given output tensor t. Args: t: the output tensor of this subgraph view. Returns: The index in the self.outputs list. Raises: Error: if t in not an output tensor.

tf.contrib.distributions.MultivariateNormalDiag.get_batch_shape() Shape of a single sample from a single event index as a TensorShape. Same meaning as batch_shape. May be only partially defined. Returns: batch_shape: TensorShape, possibly unknown.

tf.contrib.distributions.Laplace.batch_shape(name='batch_shape') Shape of a single sample from a single event index as a 1-D Tensor. The product of the dimensions of the batch_shape is the number of independent distributions of this kind the instance represents. Args: name: name to give to the op Returns: batch_shape: Tensor.

tf.contrib.bayesflow.stochastic_tensor.QuantizedDistributionTensor.distribution

tf.contrib.bayesflow.stochastic_tensor.TransformedDistributionTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

tf.contrib.distributions.Dirichlet.alpha_sum Sum of shape parameter.

tf.contrib.learn.monitors.StopAtStep.post_step(step, session) Callback after the step is finished. Called after step_end and receives session to perform extra session.run calls. If failure occurred in the process, will be called as well. Args: step: int, global step of the model. session: Session object.