latest changes from 25.07.2022

interactive/inference/generate.py

@@ -23,10 +23,10 @@ def make_shower(eph, Etrue, nEvents):
     ## LOAD ECAL GENERATOR
     mGenE = DCGAN_G(ngf, nz)
     mGenE = torch.nn.parallel.DataParallel(mGenE)
-    exp='wganHCAL_pev3'
+    exp='wganHCAL_p2critv2'
     #eph_ecal = 42
 
-    gen_checkpointECAL = torch.load('/eos/user/e/eneren/experiments/' + exp + "_generatorECAL_"+ str(eph) + ".pt", map_location=torch.device('cuda'))
+    gen_checkpointECAL = torch.load('/eos/user/e/eneren/experiments/' + exp + "_generatorE_"+ str(eph) + ".pt", map_location=torch.device('cuda'))
     mGenE.load_state_dict(gen_checkpointECAL['model_state_dict'])
     mGenE.eval()
     #####
@@ -34,13 +34,13 @@ def make_shower(eph, Etrue, nEvents):
     ## LOAD HCAL GENERATOR
     mGenH = Hcal_ecalEMB(ngf, 32, nz).to(device)
     mGenH = torch.nn.parallel.DataParallel(mGenH)
-    expH = 'wganHCAL_pev3'
+    expH = 'wganHCAL_p2critv2'
     #expH = 'wganHCALv1'
     
     Tensor = torch.cuda.FloatTensor 
     
     
-    gen_checkpointHCAL = torch.load('/eos/user/e/eneren/experiments/' + expH + "_generator_"+ str(eph) + ".pt", map_location=torch.device('cuda'))
+    gen_checkpointHCAL = torch.load('/eos/user/e/eneren/experiments/' + expH + "_generatorH_"+ str(eph) + ".pt", map_location=torch.device('cuda'))
     mGenH.load_state_dict(gen_checkpointHCAL['model_state_dict'])
     mGenH.eval()
         
@@ -230,7 +230,7 @@ def fid_scan(showers, nevents, eph_start, eph_end):
     ## LOAD ECAL GENERATOR
     mGenE = DCGAN_G(ngf, nz)
     mGenE = torch.nn.parallel.DataParallel(mGenE)
-    exp='wganHCAL_pev3'
+    exp='wganHCAL_p2critv2'
     #eph_ecal = 694
 
     
@@ -240,7 +240,7 @@ def fid_scan(showers, nevents, eph_start, eph_end):
     ## LOAD HCAL GENERATOR
     mGenH = Hcal_ecalEMB(ngf, 32, nz).to(device)
     mGenH = nn.parallel.DataParallel(mGenH)
-    expH = 'wganHCAL_pev3'
+    expH = 'wganHCAL_p2critv2'
     
     Tensor = torch.cuda.FloatTensor 
     Etrue = 50
@@ -253,11 +253,11 @@ def fid_scan(showers, nevents, eph_start, eph_end):
         #esum_down = []
         #esum_up = []
         
-        gen_checkpointHCAL = torch.load('/eos/user/e/eneren/experiments/' + expH + "_generator_"+ str(eph) + ".pt", map_location=torch.device('cuda'))
+        gen_checkpointHCAL = torch.load('/eos/user/e/eneren/experiments/' + expH + "_generatorH_"+ str(eph) + ".pt", map_location=torch.device('cuda'))
         mGenH.load_state_dict(gen_checkpointHCAL['model_state_dict'])
         mGenH.eval()
 
-        gen_checkpointECAL = torch.load('/eos/user/e/eneren/experiments/' + exp + "_generatorECAL_"+ str(eph) + ".pt", map_location=torch.device('cuda'))
+        gen_checkpointECAL = torch.load('/eos/user/e/eneren/experiments/' + exp + "_generatorE_"+ str(eph) + ".pt", map_location=torch.device('cuda'))
         mGenE.load_state_dict(gen_checkpointECAL['model_state_dict'])
         mGenE.eval()