tf.contrib.training.SequenceQueueingStateSaver.batch_size

tf.contrib.training.NextQueuedSequenceBatch.sequence_count An int32 vector, length batch_size: the sequence count

tf.contrib.training.NextQueuedSequenceBatch.total_length The lengths of the original (non-truncated) unrolled examples.

tf.contrib.training.SequenceQueueingStateSaver.__init__(batch_size, num_unroll, input_length, input_key, input_sequences, input_context, initial_states, capacity=None

tf.contrib.training.NextQueuedSequenceBatch.batch_size The batch_size of the given batch. Usually

tf.contrib.training.stratified_sample_unknown_dist(tensors, labels, probs, batch_size, enqueue_many=False, queue_capacity=16, threads_per_queue=1, name=None)

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

tf.contrib.training.NextQueuedSequenceBatch.next_key The key names of the next (in iteration) truncated unrolled examples.

tf.contrib.training.NextQueuedSequenceBatch.insertion_index The insertion indices of the examples (when they were first added)

tf.contrib.training.NextQueuedSequenceBatch.length The lengths of the given truncated unrolled examples. For