[Feature] Support dipu device (#1127)

mmengine/device/__init__.py

 # Copyright (c) OpenMMLab. All rights reserved.
 from .utils import (get_device, get_max_cuda_memory, is_cuda_available,
-                    is_mlu_available, is_mps_available, is_npu_available,
-                    is_npu_support_full_precision)
+                    is_dipu_available, is_mlu_available, is_mps_available,
+                    is_npu_available, is_npu_support_full_precision)
 
 __all__ = [
     'get_max_cuda_memory', 'get_device', 'is_cuda_available',
     'is_mlu_available', 'is_mps_available', 'is_npu_available',
-    'is_npu_support_full_precision'
+    'is_dipu_available', 'is_npu_support_full_precision'
 ]

mmengine/device/utils.py

@@ -16,6 +16,12 @@ try:
 except Exception:
     IS_NPU_AVAILABLE = False
 
+try:
+    import torch_dipu  # noqa: F401
+    IS_DIPU_AVAILABLE = True
+except Exception:
+    IS_DIPU_AVAILABLE = False
+
 
 def get_max_cuda_memory(device: Optional[torch.device] = None) -> int:
     """Returns the maximum GPU memory occupied by tensors in megabytes (MB) for
@@ -63,6 +69,10 @@ def is_mps_available() -> bool:
     return hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()
 
 
+def is_dipu_available() -> bool:
+    return IS_DIPU_AVAILABLE
+
+
 def is_npu_support_full_precision() -> bool:
     """Returns True if npu devices support full precision training."""
     version_of_support_full_precision = 220
@@ -79,6 +89,8 @@ elif is_mlu_available():
     DEVICE = 'mlu'
 elif is_mps_available():
     DEVICE = 'mps'
+elif is_dipu_available():
+    DEVICE = 'dipu'
 
 
 def get_device() -> str: