fulid resnet在flowers数据集 batchsize=128 device=CPU下，有时在运行一段时间后会出现下面错误

[ccmeteorljh]

Traceback (most recent call last):
File "resnet.py", line 225, in
run_benchmark(model_map[args.model], args)
File "resnet.py", line 190, in run_benchmark
fetch_list=[avg_cost] + accuracy.metrics)
File "/usr/local/lib/python2.7/dist-packages/paddle/v2/fluid/executor.py", line 144, in run
self.executor.run(program.desc, scope, 0, True)
paddle.v2.fluid.core.EnforceNotMet: enforce posix_memalign(&p, 4096ul, size) == 0 failed, 0 != 0
at [/paddle/paddle/memory/detail/system_allocator.cc:49]
PaddlePaddle Call Stacks:
0 0x7f4d66376b26p paddle::platform::EnforceNotMet::EnforceNotMet(std::exception_ptr::exception_ptr, char const*, int) + 486
1 0x7f4d66402e9dp paddle::memory::detail::CPUAllocator::Alloc(unsigned long&, unsigned long) + 365
2 0x7f4d66404c16p paddle::memory::detail::BuddyAllocator::RefillPool() + 86
3 0x7f4d6640543cp paddle::memory::detail::BuddyAllocator::Alloc(unsigned long) + 716
4 0x7f4d66402195p void* paddle::memory::Allocpaddle::platform::CPUPlace(paddle::platform::CPUPlace, unsigned long) + 181
5 0x7f4d6637a3f8p paddle::framework::Tensor::PlaceholderImplpaddle::platform::CPUPlace::PlaceholderImpl(paddle::platform::CPUPlace, unsigned long, std::type_index) + 56
6 0x7f4d6637a8b8p paddle::framework::Tensor::mutable_data(boost::variant<paddle::platform::GPUPlace, paddle::platform::CPUPlace, boost::detail::variant::void, boost::detail::variant::void, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>, std::type_index) + 312
7 0x7f4d6641f7c9p float* paddle::framework::Tensor::mutable_data(boost::variant<paddle::platform::GPUPlace, paddle::platform::CPUPlace, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>) + 73
8 0x7f4d668add80p paddle::operators::GemmConvGradKernel<paddle::platform::CPUPlace, float>::Compute(paddle::framework::ExecutionContext const&) const + 2208
9 0x7f4d66a76734p paddle::framework::OperatorWithKernel::Run(paddle::framework::Scope const&, paddle::platform::DeviceContext const&) const + 404
10 0x7f4d66407abdp paddle::framework::Executor::Run(paddle::framework::ProgramDescBind const&, paddle::framework::Scope*, int, bool) + 1101
11 0x7f4d663891a7p void pybind11::cpp_function::initialize<pybind11::cpp_function::initialize<void, paddle::framework::Executor, paddle::framework::ProgramDescBind const&, paddle::framework::Scope*, int, bool, pybind11::name, pybind11::is_method, pybind11::sibling>(void (paddle::framework::Executor::)(paddle::framework::ProgramDescBind const&, paddle::framework::Scope, int, bool), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&)::{lambda(paddle::framework::Executor*, paddle::framework::ProgramDescBind const&, paddle::framework::Scope*, int, bool)#1}, void, paddle::framework::Executor*, paddle::framework::ProgramDescBind const&, paddle::framework::Scope*, int, bool, pybind11::name, pybind11::is_method, pybind11::sibling>(pybind11::cpp_function::initialize<void, paddle::framework::Executor, paddle::framework::ProgramDescBind const&, paddle::framework::Scope*, int, bool, pybind11::name, pybind11::is_method, pybind11::sibling>(void (paddle::framework::Executor::)(paddle::framework::ProgramDescBind const&, paddle::framework::Scope, int, bool), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&)::{lambda(paddle::framework::Executor*, paddle::framework::ProgramDescBind const&, paddle::framework::Scope*, int, bool)#1}&&, void ()(paddle::framework::Executor, paddle::framework::ProgramDescBind const&, paddle::framework::Scope*, int, bool), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&)::{lambda(pybind11::detail::function_call&)#3}::_FUN(pybind11::detail::function_call) + 471
12 0x7f4d66384294p pybind11::cpp_function::dispatcher(_object*, _object*, _object*) + 2596
13 0x4cad00p PyEval_EvalFrameEx + 28048
14 0x4c2705p PyEval_EvalCodeEx + 597
15 0x4ca088p PyEval_EvalFrameEx + 24856
16 0x4c2705p PyEval_EvalCodeEx + 597
17 0x4ca7dfp PyEval_EvalFrameEx + 26735
18 0x4c2705p PyEval_EvalCodeEx + 597
19 0x4c24a9p PyEval_EvalCode + 25
20 0x4f19efp
21 0x4ec372p PyRun_FileExFlags + 130
22 0x4eaaf1p PyRun_SimpleFileExFlags + 401
23 0x49e208p Py_Main + 1736
24 0x7f4d7f537830p __libc_start_main + 240
25 0x49da59p _start + 41

[chengduoZH]

是运行多少个pass后出错的？看样子是分配内存的时候报错

[leanna62]

运行flowers数据集也会出现这样的问题，第1个pass运行迭代15次就会出现了，如下： @chengduoZH @dzhwinter
详细参数：vgg16， flowers，cpu， batch_size = 64
vgg16Pass = 0, Iters = 14, Loss = 4.524734, Accuracy = 0.031250
Traceback (most recent call last):
File "vgg16_modify.py", line 186, in

[chengduoZH]

没明白，你运行的是resnet50.py还是vgg16.py?

[ccmeteorljh]

我是运行fluid/resnet flower数据集的时候，在第5个pass，第71次迭代的时候出现的