other hyper parameters

learnToLearn.py

 print("META LEARNING PHASE")
 # head = l2l.algorithms.MetaSGD(head, lr=config['local_lr'],first_order=True)
 transform = l2l.optim.ModuleTransform(torch.nn.Linear)
-head = l2l.algorithms.GBML(head , transform=transform , lr=config['local_lr'] , adapt_transform=True,first_order=True)
+head = l2l.algorithms.GBML(head , transform=transform , lr=config['local_lr'] , adapt_transform=True,first_order=False)
 
 if use_cuda:
     head.cuda()

learnToLearnTest.py

     ndcgs3 = []
 
     for iterator in range(test_set_size):
-        try:
-            supp_xs = a[iterator].cuda()
-            supp_ys = b[iterator].cuda()
-            query_xs = c[iterator].cuda()
-            query_ys = d[iterator].cuda()
-        except IndexError:
-            print("index error in test method")
-            continue
+        if config['use_cuda']:
+            try:
+                supp_xs = a[iterator].cuda()
+                supp_ys = b[iterator].cuda()
+                query_xs = c[iterator].cuda()
+                query_ys = d[iterator].cuda()
+            except IndexError:
+                print("index error in test method")
+                continue
+        else:
+            try:
+                supp_xs = a[iterator]
+                supp_ys = b[iterator]
+                query_xs = c[iterator]
+                query_ys = d[iterator]
+            except IndexError:
+                print("index error in test method")
+                continue
 
         num_local_update = config['inner']
         learner = head.clone()