I had trained a model to semantic segmentiaon ,and I got a group parameters that is not bad.
When I use  ‘model.eva()’  and reload this parameters,and send testset in to this model,I will got nothing except a fully dark picture.
But when I set lr=0.0,and I send  testset in to train stage,I will got a not bad picture.This is amazing.
I had checked the input this is no worry.The question is the output.So what happen in the model when I use model.eval()
def evaluate( model):
model.eval()
model.load_state_dict(torch.load('segnet-025-0000.pth'))

loader = DataLoader(test_set('data', input_transform, target_transform),
    num_workers=4, batch_size=1, shuffle=False)

for i ,(image,path) in enumerate(loader):
    image=Variable(image).cuda()

    outputs=model(image) ####this is something wrong 

    out = color_transform(outputs[0].data.max(0)[1])        
    image=image_transform(out)   
  
    root=(path[0])            
    image.save(root+'.png')
    print(i)