from tensorflow.contrib import layers as contrib_layers

        "epsilon": batch_norm_epsilon,
        "updates_collections": batch_norm_updates_collections,
    }
    if is_training is not None:
        batch_norm_params["is_training"] = is_training

    # Set weight_decay for weights in Conv and DepthSepConv layers.
    weights_init = tf.keras.initializers.glorot_normal()
    regularizer = contrib_layers.l2_regularizer(weight_decay)
    if regularize_depthwise:
        depthwise_regularizer = regularizer
    else:
        depthwise_regularizer = None
    with slim.arg_scope(
        [slim.conv2d, slim.separable_conv2d],
        weights_initializer=weights_init,
