tf.contrib.rnn.TimeFreqLSTMCell.output_size

tf.contrib.distributions.BernoulliWithSigmoidP.is_continuous

tf.VarLenFeature.dtype Alias for field number 0

Thread* tensorflow::EnvWrapper::StartThread(const ThreadOptions &thread_options, const string &name, std::function< void()> fn) override Returns a new thread that is running fn() and is identified (for debugging/performance-analysis) by "name". Caller takes ownership of the result and must delete it eventually (the deletion will block until fn() stops running).

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

tf.contrib.distributions.Binomial.parameters Dictionary of parameters used by this Distribution.

tf.contrib.training.batch_sequences_with_states(input_key, input_sequences, input_context, input_length, initial_states, num_unroll, batch_size, num_threads=3, capacity=1000, allow_small_batch=True, pad=True, name=None) Creates batches of segments of sequential input. This method creates a SequenceQueueingStateSaver (SQSS) and adds it to the queuerunners. It returns a NextQueuedSequenceBatch. It accepts one example at a time identified by a unique input_key. input_sequence is a dict with value

tf.contrib.distributions.Categorical.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes. Args: sample_shape: TensorShape or python list/tuple. Desired shape of a call to sample(). Returns: dict of parameter name to TensorShape. Raises: ValueError: if sample_shape is a TensorShape and is not fully defined.

tf.QueueBase.queue_ref The underlying queue reference.

tf.contrib.distributions.InverseGamma.is_continuous