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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2019/05/17 08:24:26 UTC

[GitHub] [incubator-mxnet] fierceX opened a new issue #14979: [BUG] Using a package with MKL and GPU versions, using python to open a new process will cause an error

fierceX opened a new issue #14979: [BUG] Using a package with MKL and GPU versions, using python to open a new process will cause an error
URL: https://github.com/apache/incubator-mxnet/issues/14979
 
 
   Hardware and version information:
   
   ----------Python Info----------
   Version      : 3.6.8
   Compiler     : GCC 7.3.0
   Build        : ('default', 'Dec 30 2018 01:22:34')
   Arch         : ('64bit', '')
   ------------Pip Info-----------
   Version      : 19.1.1
   Directory    : /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/pip
   ----------MXNet Info-----------
   Version      : 1.4.1
   Directory    : /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/mxnet
   Hashtag not found. Not installed from pre-built package.
   ----------System Info----------
   Platform     : Linux-4.15.0-50-generic-x86_64-with-debian-buster-sid
   system       : Linux
   node         : ctmp
   release      : 4.15.0-50-generic
   version      : #54-Ubuntu SMP Mon May 6 18:46:08 UTC 2019
   ----------Hardware Info----------
   machine      : x86_64
   processor    : x86_64
   Architecture:        x86_64
   CPU op-mode(s):      32-bit, 64-bit
   Byte Order:          Little Endian
   CPU(s):              8
   On-line CPU(s) list: 0-7
   Thread(s) per core:  2
   Core(s) per socket:  4
   Socket(s):           1
   NUMA node(s):        1
   Vendor ID:           GenuineIntel
   CPU family:          6
   Model:               94
   Model name:          Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz
   Stepping:            3
   CPU MHz:             800.218
   CPU max MHz:         4000.0000
   CPU min MHz:         800.0000
   BogoMIPS:            6816.00
   Virtualization:      VT-x
   L1d cache:           32K
   L1i cache:           32K
   L2 cache:            256K
   L3 cache:            8192K
   NUMA node0 CPU(s):   0-7
   Flags:               fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb invpcid_single pti ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx rdseed adx smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp md_clear flush_l1d
   
   Python package version
   ```
   Package        Version 
   -------------- --------
   certifi        2019.3.9
   chardet        3.0.4   
   gluonnlp       0.6.0   
   graphviz       0.8.4   
   idna           2.8     
   mxnet-cu100mkl 1.4.1   
   numpy          1.14.6  
   pip            19.1.1  
   requests       2.22.0  
   setuptools     41.0.1  
   urllib3        1.25.2  
   wheel          0.33.4
   ```
   
   In a GPU package with MKL, if you create a new process in Python and use multiple processes to load data at the same time, you will get an error.
   
   ```python
   from multiprocessing import Process
   import gluonnlp as nlp
   import numpy as np
   from gluonnlp.data import SQuAD
   from mxnet import nd,gluon
   import mxnet as mx
   from mxnet.gluon import nn
   
   class Transform(object):
       def __init__(self):
           pass
   
       def __call__(self, record_index, question_id, question, context, answer_list,
                    answer_start_list):
           return np.ones((100,1)),np.ones((100,3))
   
   def train():
       train_data = SQuAD('train')
       dataloader = gluon.data.DataLoader(train_data.transform(Transform()),batch_size=128, shuffle=True, num_workers=4)
       net = nn.HybridSequential()
       net.add(nn.Dense(10))
       net.initialize(mx.init.Xavier(), ctx=mx.gpu(0))
       print(net)
   
   p = Process(target=train)
   p.start()
   p.join()
   ```
   
   ```
   Segmentation fault: 11
   
   Stack trace returned 10 entries:
   [bt] (0) /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x3f935a) [0x7ff39d25735a]
   [bt] (1) /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x3513b36) [0x7ff3a0371b36]
   [bt] (2) /lib/x86_64-linux-gnu/libc.so.6(+0x3ef20) [0x7ff3e124ff20]
   [bt] (3) /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/mxnet/libiomp5.so(+0xa9ea5) [0x7ff3dce09ea5]
   [bt] (4) /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/mxnet/libiomp5.so(+0xa9ba4) [0x7ff3dce09ba4]
   [bt] (5) /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x2da4d13) [0x7ff39fc02d13]
   [bt] (6) /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x2db56c8) [0x7ff39fc136c8]
   [bt] (7) /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/mxnet/libmxnet.so(std::shared_ptr<mxnet::engine::ThreadedEnginePerDevice::ThreadWorkerBlock<(dmlc::ConcurrentQueueType)1> > mxnet::common::LazyAllocArray<mxnet::engine::ThreadedEnginePerDevice::ThreadWorkerBlock<(dmlc::ConcurrentQueueType)1> >::Get<mxnet::engine::ThreadedEnginePerDevice::PushToExecute(mxnet::engine::OprBlock*, bool)::{lambda()#2}>(int, mxnet::engine::ThreadedEnginePerDevice::PushToExecute(mxnet::engine::OprBlock*, bool)::{lambda()#2})+0x251) [0x7ff39fc18501]
   [bt] (8) /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x2dbd359) [0x7ff39fc1b359]
   [bt] (9) /home/bird/miniconda3/envs/test/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x2da9428) [0x7ff39fc07428]
   ```
   
   If you change the mxnet version to `mxnet-cu100-1.4.1`, there will be no errors.
   Similarly, `mxnet-cu100mkl-1.5.0b20190516` will fail and `mxnet-cu100-1.5.0b20190516` will not go wrong.
   
   In addition
   Using cpu
   Remove the num_workers parameter
   Do not create a new process
   Nothing in any of the above three cases will go wrong

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