enable misc cases on XPU & use device agnostic APIs for cases in tests (#38192)

* use device agnostic APIs in tests

Signed-off-by: Matrix Yao <matrix.yao@intel.com>

* more

Signed-off-by: Matrix Yao <matrix.yao@intel.com>

* fix style

Signed-off-by: Matrix Yao <matrix.yao@intel.com>

* add reset_peak_memory_stats API

Signed-off-by: YAO Matrix <matrix.yao@intel.com>

* update

---------

Signed-off-by: Matrix Yao <matrix.yao@intel.com>
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

tests/test_modeling_common.py

@@ -73,6 +73,7 @@ from transformers.models.auto.modeling_auto import (
 )
 from transformers.testing_utils import (
     CaptureLogger,
+    backend_empty_cache,
     get_device_properties,
     hub_retry,
     is_flaky,
@@ -2652,7 +2653,7 @@ class ModelTesterMixin:
         config = self.model_tester.get_large_model_config()
 
         for model_class in self.all_parallelizable_model_classes:
-            torch.cuda.empty_cache()
+            backend_empty_cache(torch_device)
 
             # 1. single gpu memory load + unload + memory measurements
             # Retrieve initial memory usage (can easily be ~0.6-1.5GB if cuda-kernels have been preloaded by previous tests)
@@ -2668,7 +2669,7 @@ class ModelTesterMixin:
 
             del model
             gc.collect()
-            torch.cuda.empty_cache()
+            backend_empty_cache(torch_device)
 
             # 2. MP test
             # it's essential to re-calibrate the usage before the next stage
@@ -2692,7 +2693,7 @@ class ModelTesterMixin:
 
             del model
             gc.collect()
-            torch.cuda.empty_cache()
+            backend_empty_cache(torch_device)
 
     @require_torch_gpu
     @require_torch_multi_gpu