data_creator.py 文件源码

def read_and_decode_single_example(filenames, shuffle=False, num_epochs=None):
    # first construct a queue containing a list of filenames.
    # this lets a user split up there dataset in multiple files to keep size down
    # filename_queue = tf.train.string_input_producer([filename], num_epochs=10)
    filename_queue = tf.train.string_input_producer(filenames,
                                                    shuffle=shuffle, num_epochs=num_epochs)

    reader = tf.TFRecordReader()
    # One can read a single serialized example from a filename
    # serialized_example is a Tensor of type string.
    _, serialized_ex = reader.read(filename_queue)
    context, sequences = tf.parse_single_sequence_example(serialized_ex,
                                                          context_features={
                                                              "seq_length": tf.FixedLenFeature([], dtype=tf.int64)
                                                          },
                                                          sequence_features={
                                                              "seq_feature": tf.VarLenFeature(dtype=tf.int64),
                                                              "label": tf.VarLenFeature(dtype=tf.int64)
                                                          })
    return context, sequences