deprecate is_torch_bf16_available (#17738)

* deprecate is_torch_bf16_available

* address suggestions

tests/deepspeed/test_model_zoo.py

@@ -306,7 +306,7 @@ stages = [ZERO2, ZERO3]
 #
 # dtypes = [FP16]
 # so just hardcoding --fp16 for now
-# if is_torch_bf16_available():
+# if is_torch_bf16_gpu_available():
 #     dtypes += [BF16]
 
 

tests/trainer/test_trainer.py

@@ -57,7 +57,8 @@ from transformers.testing_utils import (
     require_sigopt,
     require_tokenizers,
     require_torch,
-    require_torch_bf16,
+    require_torch_bf16_cpu,
+    require_torch_bf16_gpu,
     require_torch_gpu,
     require_torch_multi_gpu,
     require_torch_non_multi_gpu,
@@ -554,7 +555,7 @@ class TrainerIntegrationPrerunTest(TestCasePlus, TrainerIntegrationCommon):
         self.assertGreater(trainer.optimizer.state_dict()["param_groups"][0]["lr"], 0)
 
     @require_torch_gpu
-    @require_torch_bf16
+    @require_torch_bf16_gpu
     def test_mixed_bf16(self):
 
         # very basic test
@@ -641,7 +642,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
         train_output = trainer.train()
         self.assertEqual(train_output.global_step, 10)
 
-    @require_torch_bf16
+    @require_torch_bf16_cpu
     @require_intel_extension_for_pytorch
     def test_number_of_steps_in_training_with_ipex(self):
         for mix_bf16 in [True, False]:
@@ -885,7 +886,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
         expected_acc = AlmostAccuracy()((pred + 1, y))["accuracy"]
         self.assertAlmostEqual(results["eval_accuracy"], expected_acc)
 
-    @require_torch_bf16
+    @require_torch_bf16_cpu
     @require_intel_extension_for_pytorch
     def test_evaluate_with_ipex(self):
         for mix_bf16 in [True, False]:
@@ -1005,7 +1006,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
         self.assertTrue(np.array_equal(labels[0], trainer.eval_dataset.ys[0]))
         self.assertTrue(np.array_equal(labels[1], trainer.eval_dataset.ys[1]))
 
-    @require_torch_bf16
+    @require_torch_bf16_cpu
     @require_intel_extension_for_pytorch
     def test_predict_with_ipex(self):
         for mix_bf16 in [True, False]:
@@ -1888,7 +1889,7 @@ class TrainerIntegrationTest(TestCasePlus, TrainerIntegrationCommon):
         self.assertGreater(orig_peak_mem, peak_mem * 2)
 
     @require_torch_gpu
-    @require_torch_bf16
+    @require_torch_bf16_gpu
     def test_bf16_full_eval(self):
         # note: most of the logic is the same as test_fp16_full_eval