Alloc Error
- Dominant language
- C++
- Stars
- 4k
- Forks
- 592
- PR merge metrics
- No merged PRs in 30d
Description
> Traceback (most recent call last):
File "main.py", line 34, in
text = lac.run(texts)
File "/home/riceball/anaconda3/envs/tf2/lib/python3.7/site-packages/LAC/lac.py", line 105, in run
crf_decode = self.predictor.run([tensor_words])
paddle.fluid.core_avx.EnforceNotMet:
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C++ Call Stacks (More useful to developers):
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0 std::string paddle::platform::GetTraceBackString(std::string const&, char const*, int)
1 paddle::memory::detail::AlignedMalloc(unsigned long)
2 paddle::memory::detail::CPUAllocator::Alloc(unsigned long*, unsigned long)
3 paddle::memory::detail::BuddyAllocator::SystemAlloc(unsigned long)
4 paddle::memory::detail::BuddyAllocator::Alloc(unsigned long)
5 void* paddle::memory::legacy::Alloc(paddle::platform::CPUPlace const&, unsigned long)
6 paddle::memory::allocation::NaiveBestFitAllocator::AllocateImpl(unsigned long)
7 paddle::memory::allocation::AllocatorFacade::Alloc(paddle::platform::Place const&, unsigned long)
8 paddle::memory::allocation::AllocatorFacade::AllocShared(paddle::platform::Place const&, unsigned long)
9 paddle::memory::AllocShared(paddle::platform::Place const&, unsigned long)
10 paddle::framework::Tensor::mutable_data(paddle::platform::Place const&, paddle::framework::proto::VarType_Type, unsigned long)
11 paddle::operators::LookupTableKernel::Compute(paddle::framework::ExecutionContext const&) const
12 std::_Function_handler, paddle::operators::LookupTableKernel, paddle::operators::LookupTableKernel >::operator()(char const*, char const*, int) const::{lambda(paddle::framework::ExecutionContext const&)#1}>::_M_invoke(std::_Any_data const&, paddle::framework::ExecutionContext const&)
13 paddle::framework::OperatorWithKernel::RunImpl(paddle::framework::Scope const&, paddle::platform::Place const&, paddle::framework::RuntimeContext*) const
14 paddle::framework::OperatorWithKernel::RunImpl(paddle::framework::Scope const&, paddle::platform::Place const&) const
15 paddle::framework::OperatorBase::Run(paddle::framework::Scope const&, paddle::platform::Place const&)
16 paddle::framework::NaiveExecutor::Run()
17 paddle::AnalysisPredictor::Run(std::vector > const&, std::vector >*, int)
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Python Call Stacks (More useful to users):
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File "/home/work/huangdingbang/anaconda3/lib/python3.7/site-packages/paddle/fluid/framework.py", line 2459, in append_op
attrs=kwargs.get("attrs", None))
File "/home/work/huangdingbang/anaconda3/lib/python3.7/site-packages/paddle/fluid/layer_helper.py", line 43, in append_op
return self.main_program.current_block().append_op(*args, **kwargs)
File "/home/work/huangdingbang/anaconda3/lib/python3.7/site-packages/paddle/fluid/layers/nn.py", line 638, in embedding
'padding_idx': padding_idx
File "../models/sequence_labeling/nets.py", line 97, in _net_conf
low=-init_bound, high=init_bound)))
File "../models/sequence_labeling/nets.py", line 136, in lex_net
return _net_conf(word)
File "/home/work/huangdingbang/models1.5/models/PaddleNLP/lexical_analysis/creator.py", line 41, in create_model
crf_decode = nets.lex_net(words, args, vocab_size, num_labels, for_infer=True, target=None)
File "inference_model.py", line 29, in save_inference_model
args, dataset.vocab_size, dataset.num_labels, mode='infer')
File "inference_model.py", line 105, in
save_inference_model(args)
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Error Message Summary:
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Error: Alloc 26685710336 error!
[Hint: Expected posix_memalign(&p, alignment, size) == 0, but received posix_memalign(&p, alignment, size):12 != 0:0.] at (/paddle/paddle/fluid/memory/detail/system_allocator.cc:59)
[operator < lookup_table > error]
请问是因为机器内存不够吗?没看懂这个报错信息
Contributor guide
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Research direction
Start with main.py and the inference path through inference_model.py, lexical_analysis/creator.py, and models/sequence_labeling/nets.py. Reproduce the lookup_table allocation failure and inspect the reported 26,685,710,336-byte allocation against the available memory and vocabulary inputs. Done means identifying a reproducible cause and documenting or validating a project-supported resolution.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100