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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/03/06 12:40:02 UTC
[GitHub] larroy opened a new issue #10004: [ARM][Jetson] assertion failed in unit test
larroy opened a new issue #10004: [ARM][Jetson] assertion failed in unit test
URL: https://github.com/apache/incubator-mxnet/issues/10004
## Description
Unit test faillure / assertion triggered in testing forward for mobilenetv2_0.25
## Environment info (Required)
```
What to do:
1. Download the diagnosis script from https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py
2. Run the script using `python diagnose.py` and paste its output here.
```
----------Python Info----------
Version : 3.5.2
Compiler : GCC 5.4.0 20160609
Build : ('default', 'Nov 23 2017 16:37:01')
Arch : ('64bit', 'ELF')
------------Pip Info-----------
Version : 9.0.1
Directory : /home/nvidia/py3/lib/python3.5/site-packages/pip
----------MXNet Info-----------
Version : 1.2.0
Directory : /home/nvidia/py3/lib/python3.5/site-packages/mxnet
Hashtag not found. Not installed from pre-built package.
----------System Info----------
Platform : Linux-4.4.38-tegra-aarch64-with-Ubuntu-16.04-xenial
system : Linux
node : tegra-ubuntu
release : 4.4.38-tegra
version : #1 SMP PREEMPT Thu Jul 20 00:49:07 PDT 2017
----------Hardware Info----------
machine : aarch64
processor : aarch64
Architecture: aarch64
Byte Order: Little Endian
CPU(s): 6
On-line CPU(s) list: 0,3-5
Off-line CPU(s) list: 1,2
Thread(s) per core: 1
Core(s) per socket: 4
Socket(s): 1
Model name: ARMv8 Processor rev 3 (v8l)
CPU max MHz: 2035.2000
CPU min MHz: 345.6000
L1d cache: 32K
L1i cache: 48K
L2 cache: 2048K
----------Network Test----------
Setting timeout: 10
Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.1431 sec, LOAD: 0.1740 sec.
Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0251 sec, LOAD: 1.0273 sec.
Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.0624 sec, LOAD: 0.1135 sec.
Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0186 sec, LOAD: 0.3011 sec.
Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0152 sec, LOAD: 0.9236 sec.
Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0215 sec, LOAD: 0.1044 sec.
```
## Build info (Required if built from source)
Cross compiled from dockerfile
MXNet commit hash:
40e6d7d37 / f973fe0
Build config:
## Error Message:
```
testing forward for mobilenetv2_0.5
testing forward for mobilenetv2_0.25
..............E.EEE..E.........../home/nvidia/py3/lib/python3.5/site-packages/mxnet/module/base_module.py:53: UserWarning: You created Module with Module(..., label_names=['softmax_label']) but input with name 'softmax_label' is not found in symbol.list_arguments(). Did you mean one of:
data
warnings.warn(msg)
/home/nvidia/py3/lib/python3.5/site-packages/mxnet/module/base_module.py:65: UserWarning: Data provided by label_shapes don't match names specified by label_names ([] vs. ['softmax_label'])
warnings.warn(msg)
./home/nvidia/py3/lib/python3.5/site-packages/mxnet/module/base_module.py:53: UserWarning: You created Module with Module(..., label_names=['softmax_label']) but input with name 'softmax_label' is not found in symbol.list_arguments(). Did you mean one of:
data
gamma
warnings.warn(msg)
...[12:28:24] /work/mxnet/src/io/iter_mnist.cc:110: MNISTIter: load 60000 images, shuffle=1, shape=(100,784)
.E.S.terminate called after throwing an instance of 'dmlc::Error'
what(): [12:29:18] /work/mxnet/dmlc-core/src/data/././strtonum.h:141: Check failed: sign == true (0 vs. 1)
Stack trace returned 9 entries:
[bt] (0) /home/nvidia/py3/lib/python3.5/site-packages/mxnet/libmxnet.so(dmlc::StackTrace()+0x44) [0x7fa1cc6550]
[bt] (1) /home/nvidia/py3/lib/python3.5/site-packages/mxnet/libmxnet.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x34) [0x7fa1cc6854]
[bt] (2) /home/nvidia/py3/lib/python3.5/site-packages/mxnet/libmxnet.so(unsigned long dmlc::data::strtouint<unsigned long>(char const*, char**, int)+0xec) [0x7fa2a50c10]
[bt] (3) /home/nvidia/py3/lib/python3.5/site-packages/mxnet/libmxnet.so(dmlc::data::LibSVMParser<unsigned long>::ParseBlock(char*, char*, dmlc::data::RowBlockContainer<unsigned long>*)+0x1f8) [0x7fa2a5fcf8]
[bt] (4) /home/nvidia/py3/lib/python3.5/site-packages/mxnet/libmxnet.so(dmlc::data::TextParserBase<unsigned long>::FillData(std::vector<dmlc::data::RowBlockContainer<unsigned long>, std::allocator<dmlc::data::RowBlockContainer<unsigned long> > >*)+0x160) [0x7fa2a633f8]
[bt] (5) /home/nvidia/py3/lib/python3.5/site-packages/mxnet/libmxnet.so(std::_Function_handler<bool (std::vector<dmlc::data::RowBlockContainer<unsigned long>, std::allocator<dmlc::data::RowBlockContainer<unsigned long> > >**), dmlc::data::ThreadedParser<unsigned long>::ThreadedParser(dmlc::data::ParserImpl<unsigned long>*)::{lambda(std::vector<dmlc::data::RowBlockContainer<unsigned long>, std::allocator<dmlc::data::RowBlockContainer<unsigned long> > >**)#1}>::_M_invoke(std::_Any_data const&, std::vector<dmlc::data::RowBlockContainer<unsigned long>, std::allocator<dmlc::data::RowBlockContainer<unsigned long> > >**)+0x30) [0x7fa2a4f684]
[bt] (6) /home/nvidia/py3/lib/python3.5/site-packages/mxnet/libmxnet.so(dmlc::ThreadedIter<std::vector<dmlc::data::RowBlockContainer<unsigned long>, std::allocator<dmlc::data::RowBlockContainer<unsigned long> > > >::Init(std::function<bool (std::vector<dmlc::data::RowBlockContainer<unsigned long>, std::allocator<dmlc::data::RowBlockContainer<unsigned long> > >**)>, std::function<void ()>)::{lambda()#1}::operator()() const+0x1b8) [0x7fa2a5d1dc]
[bt] (7) /usr/lib/aarch64-linux-gnu/libstdc++.so.6(+0xb8280) [0x7fa17a5280]
[bt] (8) /lib/aarch64-linux-gnu/libpthread.so.0(+0x6fc4) [0x7fa958ffc4]
```
## Minimum reproducible example
Run unit tests
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