Add PatchGAN42 similar to the PatchGAN in pix2pix

map2map/models/__init__.py

@@ -1,7 +1,7 @@
 from .unet import UNet
 from .vnet import VNet, VNetFat
 from .pyramid import PyramidNet
-from .patchgan import PatchGAN
+from .patchgan import PatchGAN, PatchGAN42
 
 from .conv import narrow_like
 

map2map/models/patchgan.py

@@ -10,8 +10,34 @@ class PatchGAN(nn.Module):
         self.convs = nn.Sequential(
             ConvBlock(in_chan, 32, seq='CA'),
             ConvBlock(32, 64, seq='CBA'),
-            ConvBlock(64, 128, seq='CBA'),
+            ConvBlock(64, seq='CBA'),
-            nn.Conv3d(128, out_chan, 1)
+            ConvBlock(64, 32, seq='CBA'),
+            nn.Conv3d(32, out_chan, 1),
+        )
+
+    def forward(self, x):
+        return self.convs(x)
+
+
+class PatchGAN42(nn.Module):
+    """PatchGAN similar to the one in pix2pix
+    """
+    def __init__(self, in_chan, out_chan=1):
+        super().__init__()
+
+        self.convs = nn.Sequential(
+            nn.Conv3d(in_chan, 64, 4, stride=2),
+            nn.LeakyReLU(0.2, inplace=True),
+
+            nn.Conv3d(64, 128, 4, stride=2),
+            nn.BatchNorm3d(128),
+            nn.LeakyReLU(0.2, inplace=True),
+
+            nn.Conv3d(128, 256, 4, stride=2),
+            nn.BatchNorm3d(256),
+            nn.LeakyReLU(0.2, inplace=True),
+
+            nn.Conv3d(256, out_chan, 1),
         )
 
     def forward(self, x):

map2map/train.py

@@ -58,7 +58,7 @@ def gpu_worker(local_rank, args):
         noise_chan=args.noise_chan,
         cache=args.cache,
         div_data=args.div_data,
-        rank=rank,
+        rank=args.rank,
         world_size=args.world_size,
     )
     if not args.div_data:
@@ -88,7 +88,7 @@ def gpu_worker(local_rank, args):
             noise_chan=args.noise_chan,
             cache=args.cache,
             div_data=args.div_data,
-            rank=rank,
+            rank=args.rank,
             world_size=args.world_size,
         )
         if not args.div_data: