test.py 文件源码

def _get_testing(rnn_logits,sequence_length,label,label_length):
    """Create ops for testing (all scalars): 
       loss: CTC loss function value, 
       label_error:  Batch-normalized edit distance on beam search max
       sequence_error: Batch-normalized sequence error rate
    """
    with tf.name_scope("train"):
        loss = model.ctc_loss_layer(rnn_logits,label,sequence_length) 
    with tf.name_scope("test"):
        predictions,_ = tf.nn.ctc_beam_search_decoder(rnn_logits, 
                                                   sequence_length,
                                                   beam_width=128,
                                                   top_paths=1,
                                                   merge_repeated=True)
        hypothesis = tf.cast(predictions[0], tf.int32) # for edit_distance
        label_errors = tf.edit_distance(hypothesis, label, normalize=False)
        sequence_errors = tf.count_nonzero(label_errors,axis=0)
        total_label_error = tf.reduce_sum( label_errors )
        total_labels = tf.reduce_sum( label_length )
        label_error = tf.truediv( total_label_error, 
                                  tf.cast(total_labels, tf.float32 ),
                                  name='label_error')
        sequence_error = tf.truediv( tf.cast( sequence_errors, tf.int32 ),
                                     tf.shape(label_length)[0],
                                     name='sequence_error')
        tf.summary.scalar( 'loss', loss )
        tf.summary.scalar( 'label_error', label_error )
        tf.summary.scalar( 'sequence_error', sequence_error )

    return loss, label_error, sequence_error