(pretrained=False, **kwargs)
return model
VGG 19-layer model (configuration 'E') with batch normalization
    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
VGG 19-layer model (configuration 'E') with batch normalization
    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
VGG 19 - layer model ( configuration E ) with batch normalization Args : pretrained ( bool ) : If True returns a model pre - trained on ImageNet
def multi_layer_vgg19_bn(pretrained=False, **kwargs):
    """VGG 19-layer model (configuration 'E') with batch normalization
    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
    """
    if pretrained:
        kwargs['init_weights'] = False
    model = MultiLayerVGG(make_layers(cfg['E'], batch_norm=True), **kwargs)
    if pretrained:
        model.load_pretrain_model(model_zoo.load_url(model_urls['vgg19_bn']))
    return model
def multi_layer_vgg19_bn ( pretrained = False , * * kwargs ) : if pretrained : kwargs [ 'init_weights' ] = False model = MultiLayerVGG ( make_layers ( cfg [ 'E' ] , batch_norm = True ) , * * kwargs ) if pretrained : model . load_pretrain_model ( model_zoo . load_url ( model_urls [ 'vgg19_bn' ] ) ) return model