fix test w/o gpu bug

Author: Wen-Tse Chen

openrl/envs/nlp/rewards/intent.py

@@ -41,6 +41,10 @@ def __init__(
         self.use_model_parallel = False
 
         if intent_model == "builtin_intent":
+            
+            self._device = "cpu"
+            self.use_data_parallel = False 
+            
             from transformers import GPT2Config, GPT2LMHeadModel
 
             class TestTokenizer:
@@ -66,6 +70,7 @@ def __init__(self, input_ids, attention_mask):
             self._model = GPT2LMHeadModel(config)
 
         else:
+            self._device = "cuda"
             model_path = data_abs_path(intent_model)
             self._tokenizer = AutoTokenizer.from_pretrained(intent_model)
             self._model = AutoModelForSequenceClassification.from_pretrained(model_path)
@@ -81,12 +86,10 @@ def __init__(self, input_ids, attention_mask):
                 with open(ds_config) as file:
                     ds_config = json.load(file)
 
-            self._device = "cuda"
-            self._model = self._model.to("cuda")
+            self._model = self._model.to(self._device)
             self._model, *_ = deepspeed.initialize(model=self._model, config=ds_config)
             self.use_fp16 = ds_config["fp16"]["enabled"]
         else:
-            self._device = "cuda"
             if self.use_model_parallel:
                 self._model.parallelize()
             elif self.use_data_parallel:

openrl/envs/nlp/rewards/kl_penalty.py

@@ -47,6 +47,10 @@ def __init__(
 
         # reference model
         if ref_model == "builtin_ref":
+            
+            self.device = "cpu"
+            self.use_data_parallel = False 
+            
             from transformers import GPT2Config, GPT2LMHeadModel
 
             config = GPT2Config()
@@ -77,8 +81,9 @@ def __init__(
             elif self.use_data_parallel:  # else defaults to data parallel
                 if self.use_half:
                     self._ref_net = self._ref_net.half()
-                self._ref_net = torch.nn.DataParallel(self._ref_net)
-                self._ref_net = self._ref_net.to(self.device)
+                else:
+                    self._ref_net = torch.nn.DataParallel(self._ref_net)
+                    self._ref_net = self._ref_net.to(self.device)
 
         # alpha adjustment
         self._alpha = 0.2