model.py 文件源码

def batchnorm(input, orig_graph, is_training):
    return tfl.batch_norm(
        input,
        decay=0.9,
        scale=True,
        epsilon=1E-5,
        activation_fn=None,
        param_initializers={
            'beta': get_val_or_initializer(orig_graph,
                                           tf.constant_initializer(0.),
                                           'BatchNorm/beta'),
            'gamma': get_val_or_initializer(orig_graph,
                                            tf.random_normal_initializer(1.0,
                                                                         0.02),
                                            'BatchNorm/gamma'),
            'moving_mean': get_val_or_initializer(orig_graph,
                                                  tf.constant_initializer(0.),
                                                  'BatchNorm/moving_mean'),
            'moving_variance': get_val_or_initializer(orig_graph,
                                                      tf.ones_initializer(),
                                                      'BatchNorm/moving_variance')
        },
        is_training=is_training,
        fused=True,  # new implementation with a fused kernel => speedup.
    )