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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2019/09/28 20:53:56 UTC
[GitHub] [incubator-mxnet] larroy opened a new issue #16326: Mxnet 1.5.0:
Crash while training mask-rcnn with horovod
larroy opened a new issue #16326: Mxnet 1.5.0: Crash while training mask-rcnn with horovod
URL: https://github.com/apache/incubator-mxnet/issues/16326
## Description
## Environment info (Required)
```
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 96
On-line CPU(s) list: 0-95
Thread(s) per core: 2
Core(s) per socket: 24
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 85
Model name: Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz
Stepping: 4
CPU MHz: 2787.206
BogoMIPS: 5000.00
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 32K
L1i cache: 32K
L2 cache: 1024K
L3 cache: 33792K
NUMA node0 CPU(s): 0-23,48-71
NUMA node1 CPU(s): 24-47,72-95
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves ida arat pku ospke
----------Python Info----------
Version : 3.6.8
Compiler : GCC 8.3.0
Build : ('default', 'Aug 20 2019 17:12:48')
Arch : ('64bit', 'ELF')
------------Pip Info-----------
Version : 19.2.3
Directory : /home/piotr/py3/lib/python3.6/site-packages/pip
----------MXNet Info-----------
Version : 1.5.0
Directory : /home/piotr/py3/lib/python3.6/site-packages/mxnet
Commit Hash : 75a9e187d00a8b7ebc71412a02ed0e3ae489d91f
Library : ['/home/piotr/py3/lib/python3.6/site-packages/mxnet/libmxnet.so']
Build features:
✔ CUDA
✔ CUDNN
✔ NCCL
✔ CUDA_RTC
✖ TENSORRT
✔ CPU_SSE
✔ CPU_SSE2
✔ CPU_SSE3
✔ CPU_SSE4_1
✔ CPU_SSE4_2
✖ CPU_SSE4A
✔ CPU_AVX
✖ CPU_AVX2
✖ OPENMP
✖ SSE
✔ F16C
✖ JEMALLOC
✖ BLAS_OPEN
✖ BLAS_ATLAS
✖ BLAS_MKL
✖ BLAS_APPLE
✔ LAPACK
✖ MKLDNN
✔ OPENCV
✖ CAFFE
✖ PROFILER
✔ DIST_KVSTORE
✖ CXX14
✖ INT64_TENSOR_SIZE
✔ SIGNAL_HANDLER
✖ DEBUG
----------System Info----------
Platform : Linux-4.15.0-1050-aws-x86_64-with-Ubuntu-18.04-bionic
system : Linux
node : ip-172-31-6-74
release : 4.15.0-1050-aws
version : #52-Ubuntu SMP Thu Sep 12 19:56:00 UTC 2019
----------Hardware Info----------
machine : x86_64
processor : x86_64
----------Network Test----------
Setting timeout: 10
Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0009 sec, LOAD: 0.7336 sec.
Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.0004 sec, LOAD: 0.0656 sec.
Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.0006 sec, LOAD: 0.0499 sec.
Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0005 sec, LOAD: 0.0734 sec.
Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0005 sec, LOAD: 0.1381 sec.
Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0005 sec, LOAD: 0.0575 sec.
----------Environment----------
```
Package used (Python/R/Scala/Julia):
(I'm using ...)
For Scala user, please provide:
1. Java version: (`java -version`)
2. Maven version: (`mvn -version`)
3. Scala runtime if applicable: (`scala -version`)
For R user, please provide R `sessionInfo()`:
## Build info (Required if built from source)
Installed from PIP
## Error Message:
```
[1,5]<stderr>:/home/piotr/py3/lib/python3.6/site-packages/mxnet/gluon/parameter.py:678: UserWarning: Constant parameter "maskrcnn0_rpn0_rpnanchorgenerator0_anchor_" does not support grad_req other than "null", and new value "write" is ignored.
[1,5]<stderr>: 'is ignored.'.format(self.name, req))
[1,5]<stderr>:INFO:root:Namespace(amp=False, batch_size=8, dataset='coco', disable_hybridization=False, epochs=26, executor_threads=1, gpus='0', horovod=True, kv_store='nccl', log_interval=500, lr=0.01, lr_decay=0.1, lr_decay_epoch='17,23', lr_warmup=1000, lr_warmup_factor=0.3333333333333333, momentum=0.9, network='resnet50_v1b', norm_layer=None, num_workers=4, resume='', save_interval=1, save_prefix='mask_rcnn_resnet50_v1b_coco', seed=233, start_epoch=0, static_alloc=True, use_fpn=False, val_interval=1, verbose=False, wd=0.0001)
[1,5]<stderr>:INFO:root:Start training from [Epoch 0]
[1,7]<stderr>:INFO:root:[Epoch 0 Iteration 0] Set learning rate to 0.003333333333333333
[1,0]<stderr>:INFO:root:[Epoch 0 Iteration 0] Set learning rate to 0.003333333333333333
[1,6]<stderr>:INFO:root:[Epoch 0 Iteration 0] Set learning rate to 0.003333333333333333
[1,1]<stderr>:INFO:root:[Epoch 0 Iteration 0] Set learning rate to 0.003333333333333333
[1,5]<stderr>:INFO:root:[Epoch 0 Iteration 0] Set learning rate to 0.003333333333333333
[1,3]<stderr>:INFO:root:[Epoch 0 Iteration 0] Set learning rate to 0.003333333333333333
[1,2]<stderr>:INFO:root:[Epoch 0 Iteration 0] Set learning rate to 0.003333333333333333
[1,4]<stderr>:INFO:root:[Epoch 0 Iteration 0] Set learning rate to 0.003333333333333333
[1,4]<stderr>:INFO:root:[Epoch 0 Iteration 500] Set learning rate to 0.006666666666666666
[1,2]<stderr>:INFO:root:[Epoch 0 Iteration 500] Set learning rate to 0.006666666666666666
[1,7]<stderr>:INFO:root:[Epoch 0 Iteration 500] Set learning rate to 0.006666666666666666
[1,1]<stderr>:INFO:root:[Epoch 0 Iteration 500] Set learning rate to 0.006666666666666666
[1,3]<stderr>:INFO:root:[Epoch 0 Iteration 500] Set learning rate to 0.006666666666666666
[1,5]<stderr>:INFO:root:[Epoch 0 Iteration 500] Set learning rate to 0.006666666666666666
[1,6]<stderr>:INFO:root:[Epoch 0 Iteration 500] Set learning rate to 0.006666666666666666
[1,1]<stderr>:double free or corruption (!prev)
[1,1]<stderr>:[ip-172-31-6-74:49650] *** Process received signal ***
[1,1]<stderr>:[ip-172-31-6-74:49650] Signal: Aborted (6)
[1,1]<stderr>:[ip-172-31-6-74:49650] Signal code: (-6)
[1,1]<stderr>:[ip-172-31-6-74:49650] [ 0] [1,1]<stderr>:/lib/x86_64-linux-gnu/libc.so.6(+0x3ef20)[0x7ff621a19f20]
[1,1]<stderr>:[ip-172-31-6-74:49650] [ 1] [1,1]<stderr>:/lib/x86_64-linux-gnu/libc.so.6(gsignal+0xc7)[0x7ff621a19e97]
[1,1]<stderr>:[ip-172-31-6-74:49650] [ 2] [1,1]<stderr>:/lib/x86_64-linux-gnu/libc.so.6(abort+0x141)[0x7ff621a1b801]
[1,1]<stderr>:[ip-172-31-6-74:49650] [ 3] [1,1]<stderr>:/lib/x86_64-linux-gnu/libc.so.6(+0x89897)[0x7ff621a64897]
[1,1]<stderr>:[ip-172-31-6-74:49650] [ 4] [1,1]<stderr>:/lib/x86_64-linux-gnu/libc.so.6(+0x9090a)[0x7ff621a6b90a]
[1,1]<stderr>:[ip-172-31-6-74:49650] [ 5] [1,1]<stderr>:/lib/x86_64-linux-gnu/libc.so.6(cfree+0x534)[0x7ff621a72e84]
[1,1]<stderr>:[ip-172-31-6-74:49650] [ 6] [1,1]<stderr>:/home/piotr/py3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25b7930)[0x7ff54c881930]
[1,1]<stderr>:[ip-172-31-6-74:49650] [ 7] [1,1]<stderr>:/home/piotr/py3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25bd2c6)[0x7ff54c8872c6]
[1,1]<stderr>:[ip-172-31-6-74:49650] [ 8] [1,1]<stderr>:/home/piotr/py3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25bd616)[0x7ff54c887616]
[1,1]<stderr>:[ip-172-31-6-74:49650] [ 9] [1,1]<stderr>:/home/piotr/py3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25c2a61)[0x7ff54c88ca61]
[1,1]<stderr>:[ip-172-31-6-74:49650] [10] [1,1]<stderr>:/home/piotr/py3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25c5820)[0x7ff54c88f820]
[1,1]<stderr>:[ip-172-31-6-74:49650] [11] [1,1]<stderr>:/home/piotr/py3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25c5ab6)[0x7ff54c88fab6]
[1,1]<stderr>:[ip-172-31-6-74:49650] [12] [1,1]<stderr>:/home/piotr/py3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25c0a74)[0x7ff54c88aa74]
[1,1]<stderr>:[ip-172-31-6-74:49650] [13] [1,1]<stderr>:/usr/lib/x86_64-linux-gnu/libstdc++.so.6(+0xbd9e0)[0x7ff61c3709e0]
[1,1]<stderr>:[ip-172-31-6-74:49650] [14] [1,1]<stderr>:/lib/x86_64-linux-gnu/libpthread.so.0(+0x76db)[0x7ff6217c36db]
[1,1]<stderr>:[ip-172-31-6-74:49650] [15] [1,1]<stderr>:/lib/x86_64-linux-gnu/libc.so.6(clone+0x3f)[0x7ff621afc88f]
[1,1]<stderr>:[ip-172-31-6-74:49650] *** End of error message ***
```
## Minimum reproducible example
```
time horovodrun -np 8 -H localhost:8 python train_mask_rcnn.py --dataset coco -j 4 --log-interval 500 --horovod --static-alloc 2>&1 | tee mask_rcnn_coco_horovod_noamp.log
```
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