baidu / baidu/lac

Alloc Error

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#107 3 comments 0 reactions 0 assignees View on GitHub
Dominant language
C++
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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:

--------------------------------------------
C++ Call Stacks (More useful to developers):
--------------------------------------------
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)

------------------------------------------
Python Call Stacks (More useful to users):
------------------------------------------
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)

----------------------
Error Message Summary:
----------------------
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

No contributing guide indexed for this repository

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

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