deepSpeech.py 文件源码

def _add_loss_summaries(total_loss):
    """Add summaries for losses in deepSpeech model.

    Generates moving average for all losses and associated summaries for
    visualizing the performance of the network.

    Args:
      total_loss: Total loss from loss().
    Returns:
      loss_averages_op: op for generating moving averages of losses.
    """
    # Compute the moving average of all individual losses and the total loss.
    loss_averages = tf.train.ExponentialMovingAverage(0.9, name='avg')
    losses = tf.get_collection('losses')
    loss_averages_op = loss_averages.apply(losses + [total_loss])

    # Attach a scalar summary to all individual losses and the total loss;
    # do the same for the averaged version of the losses.
    for each_loss in losses + [total_loss]:
        # Name each loss as '(raw)' and name the moving average
        # version of the loss as the original loss name.
        tf.scalar_summary(each_loss.op.name + ' (raw)', each_loss)
        tf.scalar_summary(each_loss.op.name, loss_averages.average(each_loss))

    return loss_averages_op