Format Python code according to PEP8

recbole/model/sequential_recommender/repeatnet.py

@@ -250,7 +250,9 @@ def forward(self, all_memory, last_memory, item_seq, mask=None):
         output_er = nn.Softmax(dim=-1)(output_er)
 
         batch_size, b_len = item_seq.size()
-        repeat_recommendation_decoder = torch.zeros([batch_size, self.num_item], device=self.device)
+        repeat_recommendation_decoder = torch.zeros(
+            [batch_size, self.num_item], device=self.device
+        )
         repeat_recommendation_decoder.scatter_add_(1, item_seq, output_er)
 
         return repeat_recommendation_decoder.to(self.device)
@@ -301,7 +303,9 @@ def forward(self, all_memory, last_memory, item_seq, mask=None):
         item_seq_first = item_seq[:, 0].unsqueeze(1).expand_as(item_seq)
         item_seq_first = item_seq_first.masked_fill(item_seq > 0, 0)
         item_seq_first.requires_grad_(False)
-        output_e.scatter_add_(1, item_seq + item_seq_first, float('-inf') * torch.ones_like(item_seq))
+        output_e.scatter_add_(
+            1, item_seq + item_seq_first, float("-inf") * torch.ones_like(item_seq)
+        )
         explore_recommendation_decoder = nn.Softmax(1)(output_e)
 
         return explore_recommendation_decoder