Make model compatible with output of tokenizer

model.py

@@ -42,9 +42,10 @@ class BertMesh(PreTrainedModel):
         self.linear_out = torch.nn.Linear(hidden_size, num_labels)
         self.dropout_layer = torch.nn.Dropout(self.dropout)
 
-    def forward(self, inputs):
+    def forward(self, input_ids, token_type_ids=None, attention_mask=None):
+        input_ids = torch.tensor(input_ids)
         if self.multilabel_attention:
-            hidden_states = self.bert(input_ids=inputs)[0]
+            hidden_states = self.bert(input_ids=input_ids)[0]
             attention_outs = self.multilabel_attention_layer(hidden_states)
             outs = torch.nn.functional.relu(self.linear_1(attention_outs))
             outs = self.dropout_layer(outs)