Remove redundant backend checks in training_args.py (#30999)

* Remove backend checks in training_args.py

* Expilicit initialize the device

---------
Co-authored-by: tonghengwen <tonghengwen@cambricon.com>

src/transformers/training_args.py

@@ -67,7 +67,7 @@ if is_torch_available():
     import torch
     import torch.distributed as dist
 
-    from .pytorch_utils import is_torch_greater_or_equal_than_2_0, is_torch_greater_or_equal_than_2_3
+    from .pytorch_utils import is_torch_greater_or_equal_than_2_0
 
 if is_accelerate_available():
     from accelerate.state import AcceleratorState, PartialState
@@ -1677,38 +1677,9 @@ class TrainingArguments:
                 )
                 self.accelerator_config.split_batches = self.split_batches
 
-        if (
-            self.framework == "pt"
-            and is_torch_available()
-            and (self.device.type == "cpu" and not is_torch_greater_or_equal_than_2_3)
-            and (self.device.type != "cuda")
-            and (self.device.type != "mlu")
-            and (self.device.type != "npu")
-            and (self.device.type != "xpu")
-            and (get_xla_device_type(self.device) not in ["GPU", "CUDA"])
-            and (self.fp16 or self.fp16_full_eval)
-        ):
-            raise ValueError(
-                "FP16 Mixed precision training with AMP or APEX (`--fp16`) and FP16 half precision evaluation"
-                " (`--fp16_full_eval`) can only be used on CUDA or MLU devices or NPU devices or certain XPU devices (with IPEX)."
-            )
-
-        if (
-            self.framework == "pt"
-            and is_torch_available()
-            and (self.device.type != "cuda")
-            and (self.device.type != "mlu")
-            and (self.device.type != "npu")
-            and (self.device.type != "xpu")
-            and (get_xla_device_type(self.device) not in ["GPU", "CUDA"])
-            and (get_xla_device_type(self.device) != "TPU")
-            and (self.device.type != "cpu")
-            and (self.bf16 or self.bf16_full_eval)
-        ):
-            raise ValueError(
-                "BF16 Mixed precision training with AMP (`--bf16`) and BF16 half precision evaluation"
-                " (`--bf16_full_eval`) can only be used on CUDA, XPU (with IPEX), NPU, MLU or CPU/TPU/NeuronCore devices."
-            )
+        # Initialize device before we proceed
+        if self.framework == "pt" and is_torch_available():
+            self.device
 
         if self.torchdynamo is not None:
             warnings.warn(