Refactor committee architecture to separate file

committee.py

@@ -0,0 +1,5 @@
+from net import *
+
+nets = [CNN() for _ in range(35)]
+net_dirs = [Path('./' + type(net).__name__ + str(i))
+            for i, net in enumerate(nets)]

predict.py

@@ -1,3 +1,4 @@
+from committee import net_dirs, nets
 from cuda import *
 from data import *
 from net import *
@@ -14,9 +15,6 @@
                          shuffle=False, num_workers=1, pin_memory=True)
 
 _, device = get_cuda_if_available()
-nets = [CNN(), CNN(), CNN()]
-net_dirs = [Path('./' + type(net).__name__ + str(i))
-            for i, net in enumerate(nets)]
 
 for net, net_dir in zip(nets, net_dirs):
     net.eval()

train.py

@@ -2,6 +2,7 @@
 import time
 
 import yaml
+from committee import net_dirs, nets
 from cuda import *
 from data import *
 from net import *
@@ -46,9 +47,6 @@
     validation_classes[idx] += counts
 H['validation_classes'] = validation_classes.tolist()
 
-nets = [CNN(), CNN(), CNN()]
-net_dirs = [Path('./' + type(net).__name__ + str(i))
-            for i, net in enumerate(nets)]
 for net_dir in net_dirs:
     net_dir.mkdir(parents=True, exist_ok=True)
 

validate.py

@@ -1,5 +1,6 @@
 from pathlib import Path
 
+from committee import net_dirs, nets
 from cuda import *
 from data import *
 from net import *
@@ -16,9 +17,7 @@
     config['train_path'], pretransform=True)
 validation_loader = DataLoader(dataset=validation_dataset, batch_size=1,
                                shuffle=False, num_workers=1, pin_memory=True)
-nets = [CNN(), CNN(), CNN()]
-net_dirs = [Path('./' + type(net).__name__ + str(i))
-            for i, net in enumerate(nets)]
+
 for net, net_dir in zip(nets, net_dirs):
     net.eval()
     net.to(device)