add model parameters for vgg16 to open mixed precision.

example/vgg16_cifar10/train.py

@@ -68,7 +68,8 @@ if __name__ == '__main__':
     lr = lr_steps(0, lr_max=cfg.lr_init, total_epochs=cfg.epoch_size, steps_per_epoch=50000 // cfg.batch_size)
     opt = Momentum(filter(lambda x: x.requires_grad, net.get_parameters()), Tensor(lr), cfg.momentum, weight_decay=cfg.weight_decay)
     loss = nn.SoftmaxCrossEntropyWithLogits(sparse=True, reduction='mean', is_grad=False)
-    model = Model(net, loss_fn=loss, optimizer=opt, metrics={'acc'})
+    model = Model(net, loss_fn=loss, optimizer=opt, metrics={'acc'},
+                  amp_level="O2", keep_batchnorm_fp32=False, loss_scale_manager=None)
 
     dataset = dataset.create_dataset(args_opt.data_path, cfg.epoch_size)
     batch_num = dataset.get_dataset_size()