96fad3497a4373cc289f9e7c4272d4722a22f381,src/mjsynth.py,,threaded_input_pipeline,#Any#Any#Any#Any#Any#Any#Any#,80

Before Change

            
    with tf.device(batch_device): // Create batch queue

        image, width, label, length, text, filename  = tf.train.batch_join( 
            data_tuples, 
            batch_size=batch_size,
            capacity=queue_capacity,
            allow_smaller_final_batch=final_batch,
            dynamic_pad=True)
        label = tf.deserialize_many_sparse(label, tf.int64) // post-batching...
        label = tf.cast(label, tf.int32) // for ctc_loss
    return image, width, label, length, text, filename

def _element_length_fn(image, width, label, length, text, filename, get_input):
    return width

After Change

    
    with tf.device(batch_device): // Create batch queue

        dataset = dataset.batch(batch_size)

        dataset = dataset.map(lambda image, 
                              width, label, 
                              length, text, 
                              filename: 
                              (image, width, 
                              tf.cast(tf.deserialize_many_sparse(label, tf.int64), tf.int32),
                              length, text, filename))

    return dataset

def _element_length_fn(image, width, label, length, text, filename, get_input):
    return width

Instances