train_model.py 文件源码

def __add_summaries(self,end_points,learning_rate,total_loss):
        # Add summaries for end_points (activations).

        for end_point in end_points:
            x = end_points[end_point]
            tf.summary.histogram('activations/' + end_point, x)
            tf.summary.scalar('sparsity/' + end_point,
                                            tf.nn.zero_fraction(x))
        # Add summaries for losses and extra losses.

        tf.summary.scalar('total_loss', total_loss)
        for loss in tf.get_collection('EXTRA_LOSSES'):
            tf.summary.scalar(loss.op.name, loss)

        # Add summaries for variables.
        for variable in slim.get_model_variables():
            tf.summary.histogram(variable.op.name, variable)

        return