update output dir (#3278)

PaddleCV/PaddleGAN/scripts/infer_attgan.sh

-python infer.py --model_net AttGAN --init_model output/checkpoints/119/ --dataset_dir ./data/celeba/ --image_size 128 --output ./infer_result/attgan/
+python infer.py --model_net AttGAN --init_model output/attgan/checkpoints/119/ --dataset_dir ./data/celeba/ --image_size 128 --output ./infer_result/attgan/

PaddleCV/PaddleGAN/scripts/infer_cgan.sh

-python infer.py --model_net CGAN --init_model ./output/checkpoints/19/ --n_samples 32 --noise_size 100 --output ./infer_result/c_gan/
+python infer.py --model_net CGAN --init_model ./output/c_gan/checkpoints/19/ --n_samples 32 --noise_size 100 --output ./infer_result/c_gan/

PaddleCV/PaddleGAN/scripts/infer_cyclegan.sh

-python infer.py --init_model output/checkpoints/199/ --dataset_dir data/cityscapes/ --image_size 256 --n_samples 1 --crop_size 256 --input_style B --test_list ./data/cityscapes/testB.txt --model_net CycleGAN --net_G resnet_9block  --g_base_dims 32 --output ./infer_result/cyclegan/
+python infer.py --init_model output/cyclegan/checkpoints/199/ --dataset_dir data/cityscapes/ --image_size 256 --n_samples 1 --crop_size 256 --input_style B --test_list ./data/cityscapes/testB.txt --model_net CycleGAN --net_G resnet_9block  --g_base_dims 32 --output ./infer_result/cyclegan/

PaddleCV/PaddleGAN/scripts/infer_dcgan.sh

-python infer.py --model_net DCGAN --init_model ./output/checkpoints/19/ --n_samples 32 --noise_size 100 --output ./infer_result/dcgan/
+python infer.py --model_net DCGAN --init_model ./output/dcgan/checkpoints/19/ --n_samples 32 --noise_size 100 --output ./infer_result/dcgan/

PaddleCV/PaddleGAN/scripts/infer_pix2pix.sh

-python infer.py --init_model output/checkpoints/199/ --image_size 256 --n_samples 1 --crop_size 256 --dataset_dir data/cityscapes/ --model_net Pix2pix --net_G unet_256 --test_list data/cityscapes/testB.txt --output ./infer_result/pix2pix/
+python infer.py --init_model output/pix2pix/checkpoints/199/ --image_size 256 --n_samples 1 --crop_size 256 --dataset_dir data/cityscapes/ --model_net Pix2pix --net_G unet_256 --test_list data/cityscapes/testB.txt --output ./infer_result/pix2pix/

PaddleCV/PaddleGAN/scripts/infer_stargan.sh

-python infer.py --model_net StarGAN --init_model ./output/checkpoints/19/ --dataset_dir ./data/celeba/ --image_size 128 --c_dim 5 --selected_attrs "Black_Hair,Blond_Hair,Brown_Hair,Male,Young" --output ./infer_result/stargan/
+python infer.py --model_net StarGAN --init_model ./output/stargan/checkpoints/19/ --dataset_dir ./data/celeba/ --image_size 128 --c_dim 5 --selected_attrs "Black_Hair,Blond_Hair,Brown_Hair,Male,Young" --output ./infer_result/stargan/

PaddleCV/PaddleGAN/scripts/infer_stgan.sh

-python infer.py --model_net STGAN --init_model ./output/checkpoints/19/ --dataset_dir ./data/celeba/ --image_size 128 --use_gru True --output ./infer_result/stgan/
+python infer.py --model_net STGAN --init_model ./output/stgan/checkpoints/19/ --dataset_dir ./data/celeba/ --image_size 128 --use_gru True --output ./infer_result/stgan/

PaddleCV/PaddleGAN/scripts/run_attgan.sh

-python train.py --model_net AttGAN --dataset celeba --crop_size 170 --image_size 128 --train_list ./data/celeba/list_attr_celeba.txt  --gan_mode wgan  --batch_size 32 --print_freq 1 --num_discriminator_time 5 --epoch 120 >log_out 2>log_err
+python train.py --model_net AttGAN --dataset celeba --crop_size 170 --image_size 128 --train_list ./data/celeba/list_attr_celeba.txt  --gan_mode wgan  --batch_size 32 --print_freq 1 --num_discriminator_time 5 --epoch 120 --output ./output/attgan/ >log_out 2>log_err

PaddleCV/PaddleGAN/scripts/run_cgan.sh

-python train.py --model_net CGAN --dataset mnist --noise_size 100 --batch_size 121 --epoch 20 >log_out 2>log_err
+python train.py --model_net CGAN --dataset mnist --noise_size 100 --batch_size 121 --epoch 20 --output ./output/cgan/ >log_out 2>log_err

PaddleCV/PaddleGAN/scripts/run_cyclegan.sh

-python train.py --model_net CycleGAN --dataset cityscapes --batch_size 1 --net_G resnet_9block --g_base_dim 32 --net_D basic --norm_type batch_norm --epoch 200 --image_size 286 --crop_size 256 --crop_type Random  > log_out 2>log_err 
+python train.py --model_net CycleGAN --dataset cityscapes --batch_size 1 --net_G resnet_9block --g_base_dim 32 --net_D basic --norm_type batch_norm --epoch 200 --image_size 286 --crop_size 256 --crop_type Random --output ./output/cyclegan/ > log_out 2>log_err 

PaddleCV/PaddleGAN/scripts/run_dcgan.sh

-python train.py --model_net DCGAN --dataset mnist --noise_size 100 --batch_size 128 --epoch 20 >log_out 2>log_err
+python train.py --model_net DCGAN --dataset mnist --noise_size 100 --batch_size 128 --epoch 20 --output ./output/dcgan/ >log_out 2>log_err

PaddleCV/PaddleGAN/scripts/run_pix2pix.sh

-python train.py --model_net Pix2pix --dataset cityscapes --train_list data/cityscapes/pix2pix_train_list --test_list data/cityscapes/pix2pix_test_list --crop_type Random --dropout True --gan_mode vanilla --batch_size 1 --epoch 200 --image_size 286 --crop_size 256 > log_out 2>log_err
+python train.py --model_net Pix2pix --dataset cityscapes --train_list data/cityscapes/pix2pix_train_list --test_list data/cityscapes/pix2pix_test_list --crop_type Random --dropout True --gan_mode vanilla --batch_size 1 --epoch 200 --image_size 286 --crop_size 256 --output ./output/pix2pix/ > log_out 2>log_err

PaddleCV/PaddleGAN/scripts/run_stargan.sh

-python train.py --model_net StarGAN --dataset celeba --crop_size 178 --image_size 128 --train_list ./data/celeba/list_attr_celeba.txt --batch_size 16 --epoch 20 --gan_mode wgan > log_out 2>log_err 
+python train.py --model_net StarGAN --dataset celeba --crop_size 178 --image_size 128 --train_list ./data/celeba/list_attr_celeba.txt --batch_size 16 --epoch 20 --gan_mode wgan --output ./output/stargan/ > log_out 2>log_err 

PaddleCV/PaddleGAN/scripts/run_stgan.sh

-python train.py --model_net STGAN --dataset celeba --crop_size 170 --image_size 128 --train_list ./data/celeba/list_attr_celeba.txt --gan_mode wgan  --batch_size 32 --print_freq 1 --num_discriminator_time 5 --epoch 50 >log_out 2>log_err
+python train.py --model_net STGAN --dataset celeba --crop_size 170 --image_size 128 --train_list ./data/celeba/list_attr_celeba.txt --gan_mode wgan  --batch_size 32 --print_freq 1 --num_discriminator_time 5 --epoch 50 --output ./output/stgan/ >log_out 2>log_err

PaddleCV/PaddleGAN/trainer/CGAN.py

@@ -123,7 +123,7 @@ class CGAN(object):
                 loss_name=d_trainer.d_loss.name, build_strategy=build_strategy)
 
         if self.cfg.run_test:
-            image_path = os.path.join(self.cfg.output, 'images')
+            image_path = os.path.join(self.cfg.output, 'test')
             if not os.path.exists(image_path):
                 os.makedirs(image_path)
         t_time = 0

PaddleCV/PaddleGAN/trainer/DCGAN.py

@@ -119,7 +119,7 @@ class DCGAN(object):
                 loss_name=d_trainer.d_loss.name, build_strategy=build_strategy)
 
         if self.cfg.run_test:
-            image_path = os.path.join(self.cfg.output, 'images')
+            image_path = os.path.join(self.cfg.output, 'test')
             if not os.path.exists(image_path):
                 os.makedirs(image_path)