tf.TextLineReader.read(queue, name=None) Returns the next record (key, value pair) produced by a reader. Will

tf.train.limit_epochs(tensor, num_epochs=None, name=None) Returns tensor num_epochs times and then raises an

tf.ReaderBase.restore_state(state, name=None) Restore a reader to a previously saved state. Not

tf.FixedLengthRecordReader.reader_ref Op that implements the reader.

tf.FixedLengthRecordReader.read_up_to(queue, num_records, name=None) Returns up to num_records (key, value pairs) produced by

tf.WholeFileReader.__init__(name=None) Create a WholeFileReader. Args:

tf.train.batch(tensors, batch_size, num_threads=1, capacity=32, enqueue_many=False, shapes=None, dynamic_pad=False, allow_smaller_final_batch=False, shared_name=None

tf.QueueBase.dequeue(name=None) Dequeues one element from this queue. If the queue is empty when

tf.sparse_placeholder(dtype, shape=None, name=None) Inserts a placeholder for a sparse tensor that will be always fed.

tf.train.input_producer(input_tensor, element_shape=None, num_epochs=None, shuffle=True, seed=None, capacity=32, shared_name=None, summary_name=None, name=None)