用gpu执行线性回归的例子，出现如下问题

self.executor.run(program.desc, scope, 0, True, True)
paddle.fluid.core.EnforceNotMet: enforce allocating <= available failed, 3704656494 > 3542482688
at [/paddle/paddle/fluid/platform/gpu_info.cc:119]
PaddlePaddle Call Stacks:
0 0x7f15cbcc2c76p paddle::platform::EnforceNotMet::EnforceNotMet(std::__exception_ptr::exception_ptr, char const*, int) + 486
1 0x7f15ccc7159ep paddle::platform::GpuMaxChunkSize() + 766
2 0x7f15ccba154dp paddle::memory::GetGPUBuddyAllocator(int) + 141
3 0x7f15ccba175cp void* paddle::memory::Alloc(paddle::platform::CUDAPlace, unsigned long) + 28
4 0x7f15ccb96d22p paddle::framework::Tensor::mutable_data(boost::variant, std::type_index) + 866
5 0x7f15cc2c63dfp paddle::operators::FillConstantOp::RunImpl(paddle::framework::Scope const&, boost::variant const&) const + 1007
6 0x7f15ccaf718dp paddle::framework::OperatorBase::Run(paddle::framework::Scope const&, boost::variant const&) + 205
7 0x7f15cbd5e9efp paddle::framework::Executor::RunPreparedContext(paddle::framework::ExecutorPrepareContext*, paddle::framework::Scope*, bool, bool, bool) + 255
8 0x7f15cbd5fa40p paddle::framework::Executor::Run(paddle::framework::ProgramDesc const&, paddle::framework::Scope*, int, bool, bool) + 128
9 0x7f15cbcda63bp pybind11::cpp_function::initialize(void (paddle::framework::Executor::*)(paddle::framework::ProgramDesc const&, paddle::framework::Scope*, int, bool, bool), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&)::{lambda(paddle::framework::Executor*, paddle::framework::ProgramDesc const&, paddle::framework::Scope*, int, bool, bool)#1}, void, paddle::framework::Executor*, paddle::framework::ProgramDesc const&, paddle::framework::Scope*, int, bool, bool, pybind11::name, pybind11::is_method, pybind11::sibling>(pybind11::cpp_function::initialize(void (paddle::framework::Executor::*)(paddle::framework::ProgramDesc const&, paddle::framework::Scope*, int, bool, bool), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&)::{lambda(paddle::framework::Executor*, paddle::framework::ProgramDesc const&, paddle::framework::Scope*, int, bool, bool)#1}&&, void (*)(paddle::framework::Executor*, paddle::framework::ProgramDesc const&, paddle::framework::Scope*, int, bool, bool), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&)::{lambda(pybind11::detail::function_call&)#3}::_FUN(pybind11::detail::function_call) + 555
10 0x7f15cbcd2b44p pybind11::cpp_function::dispatcher(_object*, _object*, _object*) + 2596
11 0x55e04b789d57p PyEval_EvalFrameEx + 29351
12 0x55e04b7808cap PyEval_EvalCodeEx + 1754
13 0x55e04b78824ep PyEval_EvalFrameEx + 22430
14 0x55e04b7808cap PyEval_EvalCodeEx + 1754
15 0x55e04b79c44cp
16 0x55e04b7b478ep
17 0x55e04b7b433ap
18 0x55e04b7714abp
19 0x55e04b787f60p PyEval_EvalFrameEx + 21680
20 0x55e04b7808cap PyEval_EvalCodeEx + 1754
21 0x55e04b7801e9p PyEval_EvalCode + 25
22 0x55e04b7b0bdfp
23 0x55e04b7ab952p PyRun_FileExFlags + 130
24 0x55e04b7aadcdp PyRun_SimpleFileExFlags + 397
25 0x55e04b75a58bp Py_Main + 1675
26 0x7f1610524b97p __libc_start_main + 231
27 0x55e04b759e0ap _start + 42

在终端执行export FLAGS_fraction_of_gpu_memory_to_use=0 后，问题解决。