Update for 04-17-22

config_bayesian.py

@@ -1,4 +1,6 @@
 ############### Configuration file for Bayesian ###############
+
+import os
 layer_type = 'lrt'  # 'bbb' or 'lrt'
 activation_type = 'softplus'  # 'softplus' or 'relu'
 priors={
@@ -16,4 +18,25 @@ batch_size = 256
 train_ens = 1
 valid_ens = 1
 beta_type = 0.1  # 'Blundell', 'Standard', etc. Use float for const value
-wide = 1
+
+
+with open("bay", "r") as file:
+    bay = int(file.read())
+
+if bay == 1:
+    with open("tmp", "r") as file:
+        wide = int(file.read())
+
+    if os.path.exists("tmp"):
+        os.remove("tmp")
+    else:
+        raise Exception("Tmp file not found")
+
+    print("Bayesian configured to run with width: {}".format(wide))
+
+
+if os.path.exists("bay"):
+    os.remove("bay")
+else:
+    raise Exception("Bay file not found")
+    

config_frequentist.py

@@ -1,7 +1,30 @@
 ############### Configuration file for Frequentist ###############
-n_epochs = 200
+
+import os
+n_epochs = 100
 lr = 0.001
 num_workers = 4
 valid_size = 0.2
 batch_size = 256
-wide = 1
+
+with open("frq", "r") as file:
+    frq = int(file.read())
+
+if frq == 1:
+    with open("tmp", "r") as file:
+        wide = int(file.read())
+
+    if os.path.exists("tmp"):
+        os.remove("tmp")
+    else:
+        raise Exception("Tmp file not found")
+
+    print("Frequentist configured to run with width: {}".format(wide))
+
+
+
+if os.path.exists("frq"):
+    os.remove("frq")
+else:
+    raise Exception("Frq file not found")
+

main_frequentist.py

@@ -103,16 +103,16 @@ def run(dataset, net_type):
 
         #early_stop.append(valid_acc)
         #if epoch % 4 == 0 and epoch > 0:
-            #print("Value 1: {} >= {}, Value 2: {} >= {}, Value 2: {} >= {}".format(early_stop[0],valid_acc-thrs,early_stop[1],valid_acc-thrs,early_stop[2],valid_acc-thrs))
+        #    print("Value 1: {} >= {}, Value 2: {} >= {}, Value 2: {} >= {}".format(early_stop[0],valid_acc-thrs,early_stop[1],valid_acc-thrs,early_stop[2],valid_acc-thrs))
-            #if abs(early_stop[0]) >= valid_acc-thrs and abs(early_stop[1]) >= valid_acc-thrs and abs(early_stop[2]) >= valid_acc-thrs:
+        #    if abs(early_stop[0]) >= valid_acc-thrs and abs(early_stop[1]) >= valid_acc-thrs and abs(early_stop[2]) >= valid_acc-thrs:
-                #break
+        #        break
-            #early_stop = []
+        #    early_stop = []
 
-        if train_acc >= 0.99:
+        #if train_acc >= 0.99:
-            break
+        #    break
 
         #if gpu_sample_draw.total_watt_consumed() > 100000:
-            #break
+        #    break
 
         # save model when finished
         #if epoch == n_epochs: