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/mega/test_modeling_mega.py

@@ -17,7 +17,13 @@
 import unittest
 
 from transformers import MegaConfig, is_torch_available
-from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
+from transformers.testing_utils import (
+    TestCasePlus,
+    require_torch,
+    require_torch_fp16,
+    slow,
+    torch_device,
+)
 
 from ...generation.test_utils import GenerationTesterMixin
 from ...test_configuration_common import ConfigTester
@@ -619,12 +625,12 @@ class MegaModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.check_sequence_length_beyond_max_positions(*config_and_inputs)
 
+    @require_torch_fp16
     def test_generate_fp16(self):
         config, input_ids, _, attention_mask, *_ = self.model_tester.prepare_config_and_inputs_for_decoder()
         # attention_mask = torch.LongTensor(input_ids.ne(1)).to(torch_device)
         model = MegaForCausalLM(config).eval().to(torch_device)
-        if torch_device == "cuda":
-            model.half()
+        model.half()
         model.generate(input_ids, attention_mask=attention_mask)
         model.generate(num_beams=4, do_sample=True, early_stopping=False, num_return_sequences=3)