diff --git a/Aimbot-PPO-Python/Pytorch/aimemory.py b/Aimbot-PPO-Python/Pytorch/aimemory.py
index 89aad78..8aa3ee3 100644
--- a/Aimbot-PPO-Python/Pytorch/aimemory.py
+++ b/Aimbot-PPO-Python/Pytorch/aimemory.py
@@ -107,12 +107,12 @@ class PPOMem:
                     next_done=torch.Tensor([next_done[i]]).to(self.device),
                 )
                 # send memories to training datasets
-                self.obs[roundTargetType] = torch.cat((self.obs[roundTargetType], torch.tensor(self.ob_bf[i]).to(self.device)), 0)
-                self.actions[roundTargetType] = torch.cat((self.actions[roundTargetType], torch.tensor(self.act_bf[i]).to(self.device)), 0)
-                self.dis_logprobs[roundTargetType] = torch.cat((self.dis_logprobs[roundTargetType], torch.tensor(self.dis_logprobs_bf[i]).to(self.device)), 0)
-                self.con_logprobs[roundTargetType] = torch.cat((self.con_logprobs[roundTargetType], torch.tensor(self.con_logprobs_bf[i]).to(self.device)), 0)
+                self.obs[roundTargetType] = torch.cat((self.obs[roundTargetType], torch.tensor(np.array(self.ob_bf[i])).to(self.device)), 0)
+                self.actions[roundTargetType] = torch.cat((self.actions[roundTargetType], torch.tensor(np.array(self.act_bf[i])).to(self.device)), 0)
+                self.dis_logprobs[roundTargetType] = torch.cat((self.dis_logprobs[roundTargetType], torch.tensor(np.array(self.dis_logprobs_bf[i])).to(self.device)), 0)
+                self.con_logprobs[roundTargetType] = torch.cat((self.con_logprobs[roundTargetType], torch.tensor(np.array(self.con_logprobs_bf[i])).to(self.device)), 0)
                 self.rewards[roundTargetType] = torch.cat((self.rewards[roundTargetType], thisRewardsTensor), 0)
-                self.values[roundTargetType] = torch.cat((self.values[roundTargetType], torch.tensor(self.values_bf[i]).to(self.device)), 0)
+                self.values[roundTargetType] = torch.cat((self.values[roundTargetType], torch.tensor(np.array(self.values_bf[i])).to(self.device)), 0)
                 self.advantages[roundTargetType] = torch.cat((self.advantages[roundTargetType], adv), 0)
                 self.returns[roundTargetType] = torch.cat((self.returns[roundTargetType], rt), 0)