diff --git a/bashrc.in b/bashrc.in
index f9ea5fe6..47c17939 100644
--- a/bashrc.in
+++ b/bashrc.in
@@ -7,4 +7,7 @@ export PYTHON_LIB_DIR="PYTORCH_LIB"
 export CANTERA_ROOT=LIBCANTERA_DIR
 export CANTERA_DATA=$CANTERA_ROOT/share/cantera/data
 export LD_LIBRARY_PATH=$LIBTORCH_ROOT/lib:$LD_LIBRARY_PATH
-export LD_LIBRARY_PATH=$CANTERA_ROOT/lib:$LD_LIBRARY_PATH
\ No newline at end of file
+export LD_LIBRARY_PATH=$CANTERA_ROOT/lib:$LD_LIBRARY_PATH
+export FOAM_USER_LIBBIN=pwd/platforms/lib
+export FOAM_USER_APPBIN=pwd/platforms/bin
+export LD_LIBRARY_PATH=$FOAM_USER_LIBBIN:$LD_LIBRARY_PATH
diff --git a/examples/df0DFoam/zeroD_cubicReactor/H2/pytorchIntegrator/inference.py b/examples/df0DFoam/zeroD_cubicReactor/H2/pytorchIntegrator/inference.py
index 5cfc4065..9238a55f 100644
--- a/examples/df0DFoam/zeroD_cubicReactor/H2/pytorchIntegrator/inference.py
+++ b/examples/df0DFoam/zeroD_cubicReactor/H2/pytorchIntegrator/inference.py
@@ -12,9 +12,6 @@
 
 torch.set_printoptions(precision=10)
 print('position 0 in inference.py')
-device = torch.device("cuda")
-device_ids = range(torch.cuda.device_count())
-
 
 
 class MyGELU(torch.nn.Module):
@@ -51,11 +48,49 @@ def forward(self, x):
         x = self.fc(x)
         return x
 try:
+    #load variables from constant/CanteraTorchProperties
+    path_r = r"./constant/CanteraTorchProperties"
+    with open(path_r, "r") as f:
+        data = f.read()
+        i = data.index('torchModel1') 
+        a = data.index('"',i) 
+        b = data.index('.',a+1)
+        moduleName1 = data[a+1:b]
+
+        i = data.index('torchModel2') 
+        a = data.index('"',i) 
+        b = data.index('.',a+1)
+        moduleName2 = data[a+1:b]
+
+        i = data.index('torchModel3') 
+        a = data.index('"',i) 
+        b = data.index('.',a+1)
+        moduleName3 = data[a+1:b]
+        
+        i = data.index('GPU') 
+        a = data.index(';',i) 
+        switch_GPU = data[i+4:a]
+
+    #load OpenFOAM switch
+    switch_on = ["True", "on", "yes", "y", "t", "any"]
+    switch_off = ["False", "off", "no", "n", "f", "none"]
+    if switch_GPU in switch_on:
+        device = torch.device("cuda")
+        device_ids = range(torch.cuda.device_count())
+    elif switch_GPU in switch_off:
+        device = torch.device("cpu")
+        device_ids = [0]
+    else:
+        print("invalid setting!")
+        os._exit(0)
+
+
+
     #glbal variable will only init once when called interperter
     #load parameters from json
-    setting0 = json2Parser('pytorchDNN/settings1.json')
-    setting1 = json2Parser('pytorchDNN/settings2.json')
-    setting2 = json2Parser('pytorchDNN/settings3.json')
+    setting0 = json2Parser(str("pytorchDNN/"+moduleName1+".json"))
+    setting1 = json2Parser(str("pytorchDNN/"+moduleName2+".json"))
+    setting2 = json2Parser(str("pytorchDNN/"+moduleName3+".json"))
     
     lamda = setting0.power_transform
     delta_t = setting0.delta_t
@@ -82,9 +117,9 @@ def forward(self, x):
     model0 = Net()
     model1 = Net()
     model2 = Net()
-    check_point0 = torch.load('pytorchDNN/ESH2-sub1.pt')
-    check_point1 = torch.load('pytorchDNN/ESH2-sub2.pt')
-    check_point2 = torch.load('pytorchDNN/ESH2-sub3.pt')
+    check_point0 = torch.load(str("pytorchDNN/"+moduleName1+".pt"))
+    check_point1 = torch.load(str("pytorchDNN/"+moduleName2+".pt"))
+    check_point2 = torch.load(str("pytorchDNN/"+moduleName3+".pt"))
     model0.load_state_dict(check_point0)
     model1.load_state_dict(check_point1)
     model2.load_state_dict(check_point2)
diff --git a/src/dfChemistryModel/dfChemistryModel.C b/src/dfChemistryModel/dfChemistryModel.C
index a0b4a7c9..e15d1ff9 100644
--- a/src/dfChemistryModel/dfChemistryModel.C
+++ b/src/dfChemistryModel/dfChemistryModel.C
@@ -1097,7 +1097,7 @@ Foam::scalar Foam::dfChemistryModel<ThermoType>::solve_CVODE
     const DeltaTType& deltaT
 )
 {
-    Info<<"=== begin DLB-solve === "<<endl;
+    Info<<"=== begin solve_CVODE === "<<endl;
     // CPU time analysis
     clockTime timer;
     scalar t_getProblems(0);
@@ -1119,6 +1119,7 @@ Foam::scalar Foam::dfChemistryModel<ThermoType>::solve_CVODE
 
     if(balancer_.active())
     {
+        Info<<"Now use DLB algorithm!!"<<endl;
         timer.timeIncrement();
         balancer_.updateState(allProblems);
         t_updateState = timer.timeIncrement();
@@ -1140,6 +1141,7 @@ Foam::scalar Foam::dfChemistryModel<ThermoType>::solve_CVODE
     }
     else
     {
+        Info<<"Now do not use DLB algorithm!!"<<endl;
         timer.timeIncrement();
         incomingSolutions.append(solveList(allProblems));
         t_solveBuffer = timer.timeIncrement();
@@ -1159,7 +1161,7 @@ Foam::scalar Foam::dfChemistryModel<ThermoType>::solve_CVODE
                         << endl;
     }
 
-    Info<<"=== end DLB-solve === "<<endl;
+    Info<<"=== end solve_CVODE === "<<endl;
     return updateReactionRates(incomingSolutions);
 }