rename mm to mr

README.md

@@ -37,7 +37,7 @@ If you are willing to use this code or cite the paper, please refer the followin
 $ pip install -r requirements.txt
 ```
 
-## Preprocessing 
+## Preprocessing
 ### Cityscapes
 We expect the original Cityscapes dataset to be located at `data/cityscapes/original`. Please refer to [Cityscapes Dataset](http://www.cityscapes-dataset.net/) and [mcordts/cityscapesScripts](https://github.com/mcordts/cityscapesScripts) for details.
 ```bash
@@ -82,17 +82,17 @@ $ python ./scripts/preprocess_celeba.py \
 
 ### MR-GAN
 ```bash
-$ python main.py --train --mode mr --config ./configs/{model}-{dataset}-{distribution}-{method}.yaml --log-dir ./logs/mr
+$ python main.py --mode mr --config ./configs/{model}-{dataset}-{distribution}-{method}.yaml --log-dir ./logs/mr
 ```
 
 ### Proxy MR-GAN
 Train a predictor first and determine the checkpoint where the validation loss is minimized.
 ```bash
-$ python main.py --train --mode pred --config configs/{model}-{dataset}-{distribution}-{method}.yaml --log-dir ./logs/predictor
+$ python main.py --mode pred --config configs/{model}-{dataset}-{distribution}-{method}.yaml --log-dir ./logs/predictor
 ```
-Use the checkpoint as `--pred-ckpt` to train the generator.  
+Use the checkpoint as `--pred-ckpt` to train the generator.
 ```bash
-$ python main.py --train --mode mr --config configs/{model}-{dataset}-{distribution}-{method}.yaml --log-dir ./logs/pmr --pred-ckpt ./logs/predictor/ckpt/{step}-p.pt
+$ python main.py --mode mr --config configs/{model}-{dataset}-{distribution}-{method}.yaml --log-dir ./logs/pmr --pred-ckpt ./logs/predictor/ckpt/{step}-p.pt
 ```
 
 

configs/glcic-celeba_128x128-gaussian-pmr2.yaml

@@ -41,9 +41,9 @@ model:
             recon_weight: 100
             gan_weight: 1.0
         pred:
-        mm:
-            mm_1st_weight: 1000.
-            mm_2nd_weight: 1000.
+        mr:
+            mr_1st_weight: 1000.
+            mr_2nd_weight: 1000.
             gan_weight: 1.0
             mle_weight:  0.0
 
@@ -52,8 +52,8 @@ g_pretrain_step: 0
 d_pretrain_step: 0
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 12
+num_mr: 8
+num_mr_samples: 12
 
 d_updates_per_step: 1
 g_updates_per_step: 3

configs/pix2pix-cityscapes_256x256-gaussian-mr1.yaml

@@ -42,16 +42,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 0.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 0.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 10.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-cityscapes_256x256-gaussian-mr2.yaml

@@ -42,16 +42,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 0.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 0.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 10.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-cityscapes_256x256-gaussian-pmr1.yaml

@@ -42,16 +42,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 10.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 10.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 0.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-cityscapes_256x256-gaussian-pmr2.yaml

@@ -42,16 +42,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 10.0
-            mm_2nd_weight: 10.0
+        mr:
+            mr_1st_weight: 10.0
+            mr_2nd_weight: 10.0
             gan_weight: 1.0
             mle_weight: 0.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-cityscapes_256x256-laplace-mr1.yaml

@@ -42,16 +42,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 0.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 0.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 10.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-cityscapes_256x256-laplace-mr2.yaml

@@ -42,16 +42,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 0.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 0.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 10.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-cityscapes_256x256-laplace-pmr1.yaml

@@ -42,16 +42,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 1.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 1.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 0.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-cityscapes_256x256-laplace-pmr2.yaml

@@ -42,16 +42,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 1.0
-            mm_2nd_weight: 1.0
+        mr:
+            mr_1st_weight: 1.0
+            mr_2nd_weight: 1.0
             gan_weight: 1.0
             mle_weight: 0.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-maps_256x256-gaussian-mr1.yaml

@@ -43,16 +43,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 0.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 0.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 100.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-maps_256x256-gaussian-mr2.yaml

@@ -43,16 +43,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 0.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 0.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 10.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-maps_256x256-gaussian-pmr1.yaml

@@ -43,16 +43,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 300.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 300.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 0.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-maps_256x256-gaussian-pmr2.yaml

@@ -43,16 +43,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 1000.0
-            mm_2nd_weight: 1000.0
+        mr:
+            mr_1st_weight: 1000.0
+            mr_2nd_weight: 1000.0
             gan_weight: 1.0
             mle_weight: 0.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-maps_256x256-laplace-mr1.yaml

@@ -43,16 +43,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 0.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 0.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 10.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-maps_256x256-laplace-mr2.yaml

@@ -43,16 +43,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 0.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 0.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 1.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1

configs/pix2pix-maps_256x256-laplace-pmr1.yaml

@@ -43,16 +43,16 @@ model:
             recon_weight: 100.
             gan_weight: 1.
         pred:
-        mm:
-            mm_1st_weight: 10.0
-            mm_2nd_weight: 0.0
+        mr:
+            mr_1st_weight: 10.0
+            mr_2nd_weight: 0.0
             gan_weight: 1.0
             mle_weight: 0.0
             recon_weight: 0.0  # this converts optimize_g to BASE mode
 
 batch_size: 16
-num_mm: 8
-num_mm_samples: 10
+num_mr: 8
+num_mr_samples: 10
 
 d_updates_per_step: 1
 g_updates_per_step: 1