new combinations of models

models/criticFull.py

@@ -43,13 +43,13 @@ class CriticEMB(nn.Module):
         
 
         self.conv_lin_ECAL = torch.nn.Linear(7*7*7*ndf, size_embed) 
-        self.conv_lin_HCAL = torch.nn.Linear(7*7*7*ndf, size_embed*3) 
+        self.conv_lin_HCAL = torch.nn.Linear(7*7*7*ndf, size_embed) 
         
         self.econd_lin = torch.nn.Linear(1, size_embed) # label embedding
 
-        self.fc1 = torch.nn.Linear(size_embed*5, size_embed)  # 3 components after cat
-        self.fc2 = torch.nn.Linear(size_embed,  size_embed - 8)
-        self.fc3 = torch.nn.Linear(size_embed - 8, 1)
+        self.fc1 = torch.nn.Linear(size_embed*3, size_embed)  # 3 components after cat
+        self.fc2 = torch.nn.Linear(size_embed,  size_embed - 32)
+        self.fc3 = torch.nn.Linear(size_embed - 32, 1)
 
 
     def forward(self, img_ECAL, img_HCAL, E_true):

models/generatorFull.py

@@ -24,13 +24,13 @@ class Hcal_ecalEMB(nn.Module):
         self.ln_ECAL_2 = torch.nn.LayerNorm([14,14,14])
         self.conv_ECAL_3 = torch.nn.Conv3d(ndf, ndf, kernel_size=4, stride=(2,2,2), padding=(1,1,1), bias=False)
         
-        self.conv_lin_ECAL = torch.nn.Linear(7*7*7*ndf, 8) 
+        self.conv_lin_ECAL = torch.nn.Linear(7*7*7*ndf, 64) 
         
-        self.econd_lin = torch.nn.Linear(1, 16) # label embedding
+        self.econd_lin = torch.nn.Linear(1, 8) # label embedding
 
-        self.fc1 = torch.nn.Linear(24, 16)  # 2 components after cat
-        self.fc2 = torch.nn.Linear(16,  16)
-        self.fc3 = torch.nn.Linear(16, emb_size)
+        self.fc1 = torch.nn.Linear(72, 64)  # 2 components after cat
+        self.fc2 = torch.nn.Linear(64,  32)
+        self.fc3 = torch.nn.Linear(32, emb_size)
         
         
         ## HCAL component of convolutions

wganHCAL.py

@@ -274,8 +274,8 @@ def run(args):
 
 
     ## HCAL Generator and critic
-    mCrit = CriticEMB(args.ndf).to(device)
-    mGen = Hcal_ecalEMB(args.ngf, 32, args.nz, emb_size=16).to(device)
+    mCrit = CriticEMB(args.ndf, emb_size=64).to(device)
+    mGen = Hcal_ecalEMB(args.ngf, 32, args.nz, emb_size=32).to(device)
     
     ## ECAL GENERATOR
     mGenE = DCGAN_G(args.ngf, args.nz).to(device)