feat(tests): 改进测试环境配置与设备管理

tests/conftest.py

@@ -16,8 +16,9 @@ from khaosz.trainer.data_util import *
 matplotlib.use("Agg")
 
 @pytest.fixture
-def base_test_env():
+def base_test_env(request: pytest.FixtureRequest):
-    test_dir = tempfile.mkdtemp()
+    func_name = request.function.__name__
+    test_dir = tempfile.mkdtemp(prefix=f"{func_name}_")
     config_path = os.path.join(test_dir, "config.json")
     
     n_dim_choices = [8, 16, 32]
@@ -41,12 +42,13 @@ def base_test_env():
     
     with open(config_path, 'w') as f:
         json.dump(config, f)
-    
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
     transformer_config = TransformerConfig().load(config_path)
-    model = Transformer(transformer_config)
+    model = Transformer(transformer_config).to(device=device)
     tokenizer = BpeTokenizer()
     
     yield {
+        "device": device,
         "test_dir": test_dir,
         "config_path": config_path,
         "transformer_config": transformer_config,

tests/test_callbacks.py

@@ -37,7 +37,7 @@ def test_callback_integration(base_test_env, random_dataset):
         def on_epoch_end(self, trainer, **kwargs):
             callback_calls.append('on_epoch_end')
     
-    train_config.strategy = StrategyFactory.load(base_test_env["model"], "seq")
+    train_config.strategy = StrategyFactory.load(base_test_env["model"], "seq", base_test_env["device"])
     model_parameter = ModelParameter(
         base_test_env["model"], 
         base_test_env["tokenizer"], 

tests/test_dataset_loader.py

@@ -34,7 +34,6 @@ def test_dataset_loader_random_paths(base_test_env):
         train_type="seq", 
         load_path=pkl_paths, 
         max_len=64, 
-        device="cpu"
     )
     assert loaded_dataset is not None
     assert len(loaded_dataset) > 0
@@ -62,7 +61,6 @@ def test_dpo_strategy_with_random_data(base_test_env):
         train_type="dpo", 
         load_path=pkl_path, 
         max_len=64, 
-        device="cpu"
     )
     
     assert dpo_dataset is not None

tests/test_early_stopping.py

@@ -41,7 +41,7 @@ def test_early_stopping_simulation(base_test_env):
         random_seed=42
     )
     
-    train_config.strategy = StrategyFactory.load(base_test_env["model"], "seq")
+    train_config.strategy = StrategyFactory.load(base_test_env["model"], "seq", base_test_env["device"])
     model_parameter = ModelParameter(
         base_test_env["model"], 
         base_test_env["tokenizer"], 

tests/test_module.py

@@ -10,8 +10,9 @@ from khaosz.core.generator import EmbeddingEncoderCore, GeneratorCore
 from tokenizers import pre_tokenizers
 
 @pytest.fixture
-def test_env():
+def test_env(request: pytest.FixtureRequest):
-    test_dir = tempfile.mkdtemp()
+    func_name = request.function.__name__
+    test_dir = tempfile.mkdtemp(prefix=f"{func_name}_")
     config_path = os.path.join(test_dir, "config.json")
     tokenizer_path = os.path.join(test_dir, "tokenizer.json")
     model_path = os.path.join(test_dir, "model.safetensors")

tests/test_train_config.py

@@ -47,12 +47,7 @@ def test_gradient_accumulation(base_test_env, random_dataset):
             warmup_steps=10,
             total_steps=20
         )
-        
+        train_config.strategy = StrategyFactory.load(base_test_env["model"], "seq", base_test_env["device"])
-        train_config.strategy = StrategyFactory.load(
-            base_test_env["model"], 
-            "seq"
-        )
-        
         model_parameter = ModelParameter(
             base_test_env["model"], 
             base_test_env["tokenizer"], 

tests/test_train_strategy.py

@@ -28,6 +28,7 @@ def test_multi_turn_training(base_test_env, multi_turn_dataset):
     train_config.strategy = StrategyFactory.load(
         base_test_env["model"], 
         "sft",
+        base_test_env["device"],
         bos_token_id=2,
         eos_token_id=3,
         user_token_id=1,