tf.ReaderBase.num_records_produced(name=None) Returns the number of records this reader has produced. This

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.train.batch_join(tensors_list, batch_size, capacity=32, enqueue_many=False, shapes=None, dynamic_pad=False, allow_smaller_final_batch=False, shared_name=None, name=None)

tf.TFRecordReader.num_records_produced(name=None) Returns the number of records this reader has produced. This

tf.ReaderBase.__init__(reader_ref, supports_serialize=False) Creates a new ReaderBase. Args:

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

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

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

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

tf.QueueBase.size(name=None) Compute the number of elements in this queue. Args: