move device statements outside if statements (#11292)

src/transformers/models/ctrl/modeling_ctrl.py

@@ -394,13 +394,14 @@ class CTRLModel(CTRLPreTrainedModel):
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        device = input_ids.device if input_ids is not None else inputs_embeds.device
+
         if past_key_values is None:
             past_length = 0
             past_key_values = tuple([None] * len(self.h))
         else:
             past_length = past_key_values[0][0].size(-2)
         if position_ids is None:
-            device = input_ids.device if input_ids is not None else inputs_embeds.device
             position_ids = torch.arange(past_length, input_shape[-1] + past_length, dtype=torch.long, device=device)
             position_ids = position_ids.unsqueeze(0).view(-1, input_shape[-1])
 
@@ -438,11 +439,11 @@ class CTRLModel(CTRLPreTrainedModel):
             inputs_embeds = self.w(input_ids)
         # inputs_embeds = embedded.unsqueeze(0) if len(input_ids.shape)<2 else embedded
         seq_len = input_shape[-1]
-        mask = torch.triu(torch.ones(seq_len + past_length, seq_len + past_length), 1).to(inputs_embeds.device)
+        mask = torch.triu(torch.ones(seq_len + past_length, seq_len + past_length), 1).to(device)
 
         inputs_embeds *= np.sqrt(self.d_model_size)
 
-        pos_embeds = self.pos_encoding[position_ids, :].to(inputs_embeds.device)
+        pos_embeds = self.pos_encoding[position_ids, :].to(device)
 
         hidden_states = inputs_embeds + pos_embeds + token_type_embeds
 

src/transformers/models/gpt2/modeling_gpt2.py

@@ -675,6 +675,8 @@ class GPT2Model(GPT2PreTrainedModel):
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        device = input_ids.device if input_ids is not None else inputs_embeds.device
+
         if token_type_ids is not None:
             token_type_ids = token_type_ids.view(-1, input_shape[-1])
         if position_ids is not None:
@@ -686,7 +688,6 @@ class GPT2Model(GPT2PreTrainedModel):
         else:
             past_length = past_key_values[0][0].size(-2)
         if position_ids is None:
-            device = input_ids.device if input_ids is not None else inputs_embeds.device
             position_ids = torch.arange(past_length, input_shape[-1] + past_length, dtype=torch.long, device=device)
             position_ids = position_ids.unsqueeze(0).view(-1, input_shape[-1])
 

src/transformers/models/gpt_neo/modeling_gpt_neo.py

@@ -755,6 +755,8 @@ class GPTNeoModel(GPTNeoPreTrainedModel):
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        device = input_ids.device if input_ids is not None else inputs_embeds.device
+
         if token_type_ids is not None:
             token_type_ids = token_type_ids.view(-1, input_shape[-1])
         if position_ids is not None:
@@ -766,7 +768,6 @@ class GPTNeoModel(GPTNeoPreTrainedModel):
         else:
             past_length = past_key_values[0][0].size(-2)
         if position_ids is None:
-            device = input_ids.device if input_ids is not None else inputs_embeds.device
             position_ids = torch.arange(past_length, input_shape[-1] + past_length, dtype=torch.long, device=device)
             position_ids = position_ids.unsqueeze(0).view(-1, input_shape[-1])