repair bug of skipping in sequence

sampler.py

@@ -12,14 +12,26 @@ def random_neq(l, r, s, user_train,usernum):
     # while t in s:
     #     t = np.random.randint(l, r)
     # return t
-    user = np.random.choice(1, usernum + 1)
-    candid_item = user_train[user][np.random.randint(0, len(user_train[user]))]
-
-    while candid_item in s:
-        user = np.random.randint(1, usernum + 1)
-        candid_item = user_train[user][np.random.randint(0, len(user_train[user]))]
-    return candid_item
-
+    # user = np.random.choice(1, usernum + 1)
+
+    # user = random.randint(1,usernum+1)
+    # while len(user_train[user])<3:
+    #     user = random.randint(1, usernum + 1)
+    # candid_item = user_train[user][random.randint(0, len(user_train[user])-1)]
+    #
+    # while candid_item in s:
+    #     while len(user_train[user]) < 3:
+    #         user = random.randint(1, usernum + 1)
+    #     candid_item = user_train[user][random.randint(0, len(user_train[user])-1)]
+    # return candid_item
+
+    user = random.choice(list(user_train.keys()))
+    item = random.choice(user_train[user])
+
+    while item in s:
+        user = random.choice(list(user_train.keys()))
+        item = random.choice(user_train[user])
+    return item
 
 def random_negetive_batch(l, r, s, user_train,usernum, batch_users):
     user = np.random.choice(batch_users)
@@ -40,7 +52,7 @@ def sample_function_mixed(user_train, usernum, itemnum, batch_size, maxlen, resu
 
             seq = np.zeros([maxlen], dtype=np.int32)
             pos = np.zeros([maxlen], dtype=np.int32)
-            neg = np.zeros([maxlen*number_of_neg], dtype=np.int32)
+            neg = np.zeros([(maxlen-1)*number_of_neg + 1], dtype=np.int32)
 
             if len(user_train[user]) < maxlen:
                 nxt_idx = len(user_train[user]) - 1
@@ -51,7 +63,7 @@ def sample_function_mixed(user_train, usernum, itemnum, batch_size, maxlen, resu
             idx = maxlen - 1
 
             ts = set(user_train[user])
-            for i in reversed(user_train[user][min(0, nxt_idx - 1 - maxlen) : nxt_idx - 1]):
+            for i in reversed(user_train[user][(nxt_idx - maxlen) : nxt_idx ]):
                 seq[idx] = i
                 pos[idx] = nxt
                 # if nxt != 0: neg[idx] = random_neq(1, itemnum + 1, ts, user_train,usernum)
@@ -74,7 +86,7 @@ def sample_function_mixed(user_train, usernum, itemnum, batch_size, maxlen, resu
             #     support_negative_triples.append([seq[-1], curr_rel, neg[idx]])
             for j in range(number_of_neg):
                 for idx in range(maxlen-1):
-                    support_negative_triples.append([seq[idx], curr_rel, neg[j*maxlen + idx]])
+                    support_negative_triples.append([seq[idx], curr_rel, neg[j*(maxlen-1) + idx]])
 
             query_triples.append([seq[-1],curr_rel,pos[-1]])
             negative_triples.append([seq[-1],curr_rel,neg[-1]])

utils.py

@@ -148,9 +148,13 @@ class DataLoader(object):
 
         # for idx in range(len(neg)):
         #     support_negative_triples.append([seq[-1],curr_rel,neg[idx]])
+        # print("injam",self.maxlen,list(range(self.maxlen-1)))
+        # print("====")
         for j in range(self.number_of_neg):
             for idx in range(self.maxlen-1):
-                support_negative_triples.append([seq[idx], curr_rel, neg[j * self.maxlen + idx]])
+                # print(j * self.maxlen + idx)
+                support_negative_triples.append([seq[idx], curr_rel, neg[j * (self.maxlen-1) + idx]])
+        # print("=end=\n\n")
 
         rated = ts
         rated.add(0)