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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/03/30 09:25:48 UTC

[GitHub] vascokk opened a new issue #10338: NDArray saved in Python cannot be loaded in Scala

vascokk opened a new issue #10338: NDArray saved in Python cannot be loaded in Scala
URL: https://github.com/apache/incubator-mxnet/issues/10338
 
 
   
   ## Description
   I am trying to convert a numpy array into an ndarray and save it. I intend to use the ndaray file in Scala, but getting src/ndarray/ndarray.cc:672: Check failed: fi->Read(data) Invalid NDArray file format.
   
   ## Environment info (Required)
   Architecture:        x86_64
   CPU op-mode(s):      32-bit, 64-bit
   Byte Order:          Little Endian
   CPU(s):              4
   On-line CPU(s) list: 0-3
   Thread(s) per core:  1
   Core(s) per socket:  4
   Socket(s):           1
   NUMA node(s):        1
   Vendor ID:           GenuineIntel
   CPU family:          6
   Model:               60
   Model name:          Intel(R) Core(TM) i5-4570 CPU @ 3.20GHz
   Stepping:            3
   CPU MHz:             3192.584
   CPU max MHz:         3600.0000
   CPU min MHz:         800.0000
   BogoMIPS:            6385.16
   Virtualization:      VT-x
   L1d cache:           32K
   L1i cache:           32K
   L2 cache:            256K
   L3 cache:            6144K
   NUMA node0 CPU(s):   0-3
   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 arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm abm cpuid_fault epb invpcid_single pti retpoline tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm xsaveopt dtherm ida arat pln pts
   ----------Python Info----------
   ('Version      :', '2.7.14')
   ('Compiler     :', 'GCC 7.2.0')
   ('Build        :', ('default', 'Sep 23 2017 22:06:14'))
   ('Arch         :', ('64bit', ''))
   ------------Pip Info-----------
   ('Version      :', '9.0.3')
   ('Directory    :', '/usr/local/lib/python2.7/dist-packages/pip')
   ----------MXNet Info-----------
   ('Version      :', '1.1.0')
   ('Directory    :', '/usr/local/lib/python2.7/dist-packages/mxnet')
   ('Commit Hash   :', '07a83a0325a3d782513a04f47d711710972cb144')
   ----------System Info----------
   ('Platform     :', 'Linux-4.13.0-37-generic-x86_64-with-Ubuntu-17.10-artful')
   ('system       :', 'Linux')
   ('node         :', 'desktop-102016')
   ('release      :', '4.13.0-37-generic')
   ('version      :', '#42-Ubuntu SMP Wed Mar 7 14:13:23 UTC 2018')
   ----------Hardware Info----------
   ('machine      :', 'x86_64')
   ('processor    :', 'x86_64')
   ----------Network Test----------
   Setting timeout: 10
   Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0008 sec, LOAD: 0.6838 sec.
   Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0010 sec, LOAD: 0.1299 sec.
   Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0004 sec, LOAD: 0.8468 sec.
   Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0006 sec, LOAD: 0.0610 sec.
   Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.0014 sec, LOAD: 0.0648 sec.
   Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.0016 sec, LOAD: 0.7765 sec.
   
   Package used (Python/R/Scala/Julia):
   Python 2.7
   
   For Scala user, please provide:
   1. Java version: (`java -version`): 
   
   java version "1.8.0_144"
   Java(TM) SE Runtime Environment (build 1.8.0_144-b01)
   Java HotSpot(TM) 64-Bit Server VM (build 25.144-b01, mixed mode)
   
   
   2. Maven version: (`mvn -version`)
   Apache Maven 3.5.0
   Maven home: /usr/share/maven
   Java version: 1.8.0_112, vendor: Oracle Corporation
   Java home: /usr/local/java/jdk1.8.0_112/jre
   Default locale: en_IE, platform encoding: UTF-8
   OS name: "linux", version: "4.13.0-37-generic", arch: "amd64", family: "unix"
   
   3. Scala runtime if applicable: (`scala -version`)
   Scala code runner version 2.11.8 -- Copyright 2002-2016, LAMP/EPFL
   
   For R user, please provide R `sessionInfo()`:
   
   ## Build info (Required if built from source)
   
   Compiler (gcc/clang/mingw/visual studio):
   
   MXNet commit hash:
   (Paste the output of `git rev-parse HEAD` here.)
   
   Build config:
   (Paste the content of config.mk, or the build command.)
   
   ## Error Message:
   [10:10:45] /home/ubuntu/mxnet/dmlc-core/include/dmlc/logging.h:300: [10:10:45] src/ndarray/ndarray.cc:672: Check failed: fi->Read(data) Invalid NDArray file format
   
   Stack trace returned 5 entries:
   [bt] (0) /tmp/mxnet7044930640479576680/mxnet-scala(_ZN4dmlc15LogMessageFatalD1Ev+0x39) [0x7f529b12e6b9]
   [bt] (1) /tmp/mxnet7044930640479576680/mxnet-scala(_ZN5mxnet7NDArray4LoadEPN4dmlc6StreamEPSt6vectorIS0_SaIS0_EEPS4_INSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEESaISD_EE+0x207) [0x7f529ba4e747]
   [bt] (2) /tmp/mxnet7044930640479576680/mxnet-scala(MXNDArrayLoad+0x4cd) [0x7f529bd7c26d]
   [bt] (3) /tmp/mxnet7044930640479576680/mxnet-scala(Java_ml_dmlc_mxnet_LibInfo_mxNDArrayLoad+0x64) [0x7f529b122254]
   [bt] (4) [0x7f52f9017a34]
   
   Exception in thread "main" ml.dmlc.mxnet.MXNetError: [10:10:45] src/ndarray/ndarray.cc:672: Check failed: fi->Read(data) Invalid NDArray file format
   
   
   ## Minimum reproducible example
   (If you are using your own code, please provide a short script that reproduces the error. Otherwise, please provide link to the existing example.)
   
   ## Steps to reproduce
   (Paste the commands you ran that produced the error.)
   
   $ python
   Python 2.7.14 (default, Sep 23 2017, 22:06:14) 
   [GCC 7.2.0] on linux2
   Type "help", "copyright", "credits" or "license" for more information.
   >>> import mxnet as mx
   >>> a = mx.nd.ones((100, 50))
   >>> mx.nd.save("a", [a])
   
   then in Scala:
   
   import ml.dmlc.mxnet._
   val a = NDArray.load("a")
   
   ## What have you tried to solve it?
   

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