diff --git a/python/paddle/__init__.py b/python/paddle/__init__.py
index e707de8e068640e28d3a06d539e33f767d7ab2b3..93b9a71ed7dac273c297d8d758423ddfc18666ee 100755
--- a/python/paddle/__init__.py
+++ b/python/paddle/__init__.py
@@ -257,6 +257,7 @@ from .tensor.stat import numel  #DEFINE_ALIAS
 from .device import get_cudnn_version
 from .device import set_device
 from .device import get_device
+from .device import is_compiled_with_cuda  #DEFINE_ALIAS
 from .device import is_compiled_with_xpu
 from .device import XPUPlace
 # from .tensor.tensor import Tensor        #DEFINE_ALIAS
diff --git a/python/paddle/device.py b/python/paddle/device.py
index 46d0ff7bedcecfefc7d054b0ccbcbf100c2fa0f6..c2f331caa8ab3e338d7d1148a15c1de1309aec34 100644
--- a/python/paddle/device.py
+++ b/python/paddle/device.py
@@ -18,6 +18,7 @@ import re
 from paddle.fluid import core
 from paddle.fluid import framework
 from paddle.fluid.dygraph.parallel import ParallelEnv
+from paddle.fluid.framework import is_compiled_with_cuda  #DEFINE_ALIAS
 
 __all__ = [
     'get_cudnn_version',
@@ -31,7 +32,7 @@ __all__ = [
     #            'cuda_places',
     #            'CUDAPinnedPlace',
     #            'CUDAPlace',
-    #            'is_compiled_with_cuda'
+    'is_compiled_with_cuda'
 ]
 
 _cudnn_version = None
diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py
index 2afe3ac3d76899775e480d53d71dd65a3757092c..d4a4b135cdb5c6d9d25b564661289892e3f57339 100644
--- a/python/paddle/fluid/framework.py
+++ b/python/paddle/fluid/framework.py
@@ -360,13 +360,13 @@ def is_compiled_with_cuda():
     """
     Whether this whl package can be used to run the model on GPU.
 
-    Returns (bool): support gpu or not.
+    Returns (bool): `True` if CUDA is currently available, otherwise `False`.
 
     Examples:
         .. code-block:: python
 
-            import paddle.fluid as fluid
-            support_gpu = fluid.is_compiled_with_cuda()
+            import paddle
+            support_gpu = paddle.is_compiled_with_cuda()
     """
     return core.is_compiled_with_cuda()