import paddle.fluid as fluid
support_gpu = fluid.is_compiled_with_cuda()
place = fluid.CPUPlace()
if support_gpu:
    place = fluid.CUDAPlace(0)
# if GPU is supported, the three OPs below will be automatically assigned to CUDAPlace(0)
data1 = fluid.layers.fill_constant(shape=[1, 3, 8, 8], value=0.5, dtype='float32')
data2 = fluid.layers.fill_constant(shape=[1, 3, 5, 5], value=0.5, dtype='float32')
shape = fluid.layers.shape(data2)
with fluid.device_guard("cpu"):
    # Ops created here will be placed on CPUPlace
    shape = fluid.layers.slice(shape, axes=[0], starts=[0], ends=[4])
with fluid.device_guard('gpu'):
    # if GPU is supported, OPs created here will be placed on CUDAPlace(0), otherwise on CPUPlace
    out = fluid.layers.crop_tensor(data1, shape=shape)
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
result = exe.run(fetch_list=[out])