def parse_sequence_example(serialized, image_feature, caption_feature):
 (context, sequence) = tf.parse_single_sequence_example(serialized, context_features={image_feature: tf.FixedLenFeature([], dtype=tf.string)}, sequence_features={caption_feature: tf.FixedLenSequenceFeature([], dtype=tf.int64)})
 encoded_image = context[image_feature]
 caption = sequence[caption_feature]
 return (encoded_image, caption)

def parse_sequence_example ( serialized , image_feature , caption_feature ) : ( context , sequence ) = tf . parse_single_sequence_example ( serialized , context_features = { image_feature : tf . FixedLenFeature ( [ ] , dtype = tf . string ) } , sequence_features = { caption_feature : tf . FixedLenSequenceFeature ( [ ] , dtype = tf . int64 ) } ) encoded_image = context [ image_feature ] caption = sequence [ caption_feature ] return ( encoded_image , caption )
parses a tensorflow .