device agnostic models testing (#27146)

* device agnostic models testing

* add decorator `require_torch_fp16`

* make style

* apply review suggestion

* Oops, the fp16 decorator was misused

tests/models/blip_2/test_modeling_blip_2.py

@@ -23,7 +23,13 @@ import numpy as np
 import requests
 
 from transformers import CONFIG_MAPPING, Blip2Config, Blip2QFormerConfig, Blip2VisionConfig
-from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
+from transformers.testing_utils import (
+    require_torch,
+    require_torch_multi_accelerator,
+    require_vision,
+    slow,
+    torch_device,
+)
 from transformers.utils import is_torch_available, is_vision_available
 
 from ...test_configuration_common import ConfigTester
@@ -934,8 +940,8 @@ class Blip2ModelIntegrationTest(unittest.TestCase):
         self.assertEqual(predictions[0].tolist(), [0, 2335, 1556, 28, 1782, 30, 8, 2608, 1])
         self.assertEqual(predictions[1].tolist(), [0, 2335, 1556, 28, 1782, 30, 8, 2608, 1])
 
-    @require_torch_multi_gpu
-    def test_inference_opt_multi_gpu(self):
+    @require_torch_multi_accelerator
+    def test_inference_opt_multi_accelerator(self):
         processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b")
         model = Blip2ForConditionalGeneration.from_pretrained(
             "Salesforce/blip2-opt-2.7b", torch_dtype=torch.float16, device_map="balanced"
@@ -966,8 +972,8 @@ class Blip2ModelIntegrationTest(unittest.TestCase):
         )
         self.assertEqual(generated_text, "it's not a city, it's a beach")
 
-    @require_torch_multi_gpu
-    def test_inference_t5_multi_gpu(self):
+    @require_torch_multi_accelerator
+    def test_inference_t5_multi_accelerator(self):
         processor = Blip2Processor.from_pretrained("Salesforce/blip2-flan-t5-xl")
         device_map = device_map = {
             "query_tokens": 0,