tf.QueueBase.size(name=None) Compute the number of elements in this queue. Args: name: A name for the operation (optional). Returns: A scalar tensor containing the number of elements in this queue.

class tf.contrib.training.SequenceQueueingStateSaver SequenceQueueingStateSaver provides access to stateful values from input. This class is meant to be used instead of, e.g., a Queue, for splitting variable-length sequence inputs into segments of sequences with fixed length and batching them into mini-batches. It maintains contexts and state for a sequence across the segments. It can be used in conjunction with a QueueRunner (see the example below). The SequenceQueueingStateSaver (SQSS) accep

tf.contrib.graph_editor.SubGraphView.__bool__() Allows for implicit boolean conversion.

tf.contrib.distributions.Categorical.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of parameters given the desired shape of a call to sample(). Subclasses should override static method _param_shapes. Args: sample_shape: Tensor or python list/tuple. Desired shape of a call to sample(). name: name to prepend ops with. Returns: dict of parameter name to Tensor shapes.

bool tensorflow::PartialTensorShape::IsCompatibleWith(const PartialTensorShape &shape) const Return true iff the ranks match, and if the dimensions all either match or one is unknown.

tf.contrib.graph_editor.matcher.control_input_ops(*args) Add input matches.

tf.contrib.bayesflow.stochastic_tensor.LaplaceTensor.dtype

tf.contrib.distributions.Binomial.name Name prepended to all ops created by this Distribution.

tf.contrib.distributions.TransformedDistribution.log_pdf(value, name='log_pdf') Log probability density function. 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. Raises: TypeError: if not is_continuous.

tf.errors.CancelledError.__init__(node_def, op, message) Creates a CancelledError.