2.0 API: device_guard

doc/paddle/api/alias_api_mapping

@@ -88,6 +88,7 @@ paddle.device.set_device	paddle.set_device
 paddle.device.get_cudnn_version	paddle.get_cudnn_version
 paddle.device.XPUPlace	paddle.XPUPlace
 paddle.device.is_compiled_with_xpu	paddle.is_compiled_with_xpu
+paddle.fluid.framework.device_guard	paddle.static.device_guard
 paddle.fluid.framework.is_compiled_with_cuda	paddle.is_compiled_with_cuda,paddle.device.is_compiled_with_cuda
 paddle.fluid.layers.log_loss	paddle.nn.functional.log_loss,paddle.nn.functional.loss.log_loss
 paddle.fluid.layers.softmax_with_cross_entropy	paddle.nn.functional.softmax_with_cross_entropy,paddle.nn.functional.loss.softmax_with_cross_entropy

doc/paddle/api/paddle/fluid/framework/device_guard_cn.rst

@@ -0,0 +1,41 @@
+.. _cn_api_device_guard:
+
+device_guard
+-------------------------------
+
+**注意：该API仅支持静态图模式**
+
+.. py:function:: paddle.static.device_guard(device=None)
+
+一个用于指定OP运行设备的上下文管理器。
+
+参数：
+    - **device** (str|None) – 指定上下文中使用的设备。它可以是'cpu'或者'gpu‘，当它被设置为'cpu'或者'gpu'时，创建在该上下文中的OP将被运行在CPUPlace或者CUDAPlace上。若设置为'gpu'，同时程序运行在单卡模式下，设备的索引将与执行器的设备索引保持一致。默认值：None，在该上下文中的OP将被自动地分配设备。
+
+**代码示例**
+
+.. code-block:: python
+
+    import paddle
+
+    paddle.enable_static()
+    support_gpu = paddle.is_compiled_with_cuda()
+    place = paddle.CPUPlace()
+    if support_gpu:
+        place = paddle.CUDAPlace(0)
+
+    # if GPU is supported, the three OPs below will be automatically assigned to CUDAPlace(0)
+    data1 = paddle.full(shape=[1, 3, 8, 8], fill_value=0.5, dtype='float32')
+    data2 = paddle.full(shape=[1, 3, 64], fill_value=0.5, dtype='float32')
+    shape = paddle.shape(data2)
+
+    with paddle.static.device_guard("cpu"):
+        # Ops created here will be placed on CPUPlace
+        shape = paddle.slice(shape, axes=[0], starts=[0], ends=[4])
+    with paddle.static.device_guard('gpu'):
+        # if GPU is supported, OPs created here will be placed on CUDAPlace(0), otherwise on CPUPlace
+        out = paddle.reshape(data1, shape=shape)
+
+    exe = paddle.static.Executor(place)
+    exe.run(paddle.static.default_startup_program())
+    result = exe.run(fetch_list=[out])