ㄱㅈ같은 ..validation

• epoch 10개 당 result 생기는건

    if epoch == 10:
        for param in model.parameters():
            param.requires_grad =True
    if (epoch % args.save_freq) ==0: # 중간에 이미지 save 

        for batch_idx, (X_batch, y_batch, *rest) in enumerate(valloader): # Validation Data 
            # print(batch_idx)
            if isinstance(rest[0][0], str):
                        image_filename = rest[0][0]
            else:
                        image_filename = '%s.png' % str(batch_idx + 1).zfill(3)

            X_batch = Variable(X_batch.to(device='cuda')) # validation data의 x 
            y_batch = Variable(y_batch.to(device='cuda')) # validation data의 label 
            # start = timeit.default_timer()
            y_out = model(X_batch) # 학습 결과 
            # stop = timeit.default_timer()
            # print('Time: ', stop - start) 
            tmp2 = y_batch.detach().cpu().numpy() # validation data의 y 
            tmp = y_out.detach().cpu().numpy() 
            tmp[tmp>=0.5] = 1
            tmp[tmp<0.5] = 0
            tmp2[tmp2>0] = 1
            tmp2[tmp2<=0] = 0
            tmp2 = tmp2.astype(int)
            tmp = tmp.astype(int)

            # print(np.unique(tmp2))
            yHaT = tmp
            yval = tmp2

            epsilon = 1e-20
            
            del X_batch, y_batch,tmp,tmp2, y_out

            
            yHaT[yHaT==1] =255
            yval[yval==1] =255
            fulldir = direc+"/{}/".format(epoch)
            # print(fulldir+image_filename)
            if not os.path.isdir(fulldir):
                
                os.makedirs(fulldir)
            
            cv2.imwrite(fulldir+image_filename, yHaT[0,1,:,:]) 
            # cv2.imwrite(fulldir+'/gt_{}.png'.format(count), yval[0,:,:])
        fulldir = direc+"/{}/".format(epoch)
        torch.save(model.state_dict(), fulldir+args.modelname+".pth")
        torch.save(model.state_dict(), direc+"/"+args.modelname+"_final_model.pth")
            

10개 epoch 당 1개씩 생성되는 거 = Validation set에 대해서임.