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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2019/07/31 00:17:11 UTC

[GitHub] [incubator-mxnet] PatriciaXiao edited a comment on issue #15629: DataLoader Error using Multi processing

PatriciaXiao edited a comment on issue #15629: DataLoader Error using Multi processing
URL: https://github.com/apache/incubator-mxnet/issues/15629#issuecomment-516643562
 
 
   In addition to what is discussed above: it doesn't matter if it is an EC2 P3.16 or P3.2.
   
   In fact the same thing happened to me on P3.2 after I tried to upgrade Python to 3.7 using anaconda. Latter on I tried get rid of these bugs by using Python 3.6 again but it seems that these issues remain foreverly here from now on.
   
   So frustrating:
   
   '''shell
   Segmentation fault: 11
   
   Stack trace:
     [bt] (0) /home/ubuntu/anaconda3/lib/python3.7/site-packages/mxnet/libmxnet.so(+0x2e6b160) [0x7f07f023f160]
     [bt] (1) /lib/x86_64-linux-gnu/libc.so.6(+0x354b0) [0x7f082d42a4b0]
     [bt] (2) /home/ubuntu/anaconda3/lib/python3.7/site-packages/numpy/../../../libiomp5.so(+0xa82a8) [0x7f082b9eb2a8]
     [bt] (3) /home/ubuntu/anaconda3/lib/python3.7/site-packages/numpy/../../../libiomp5.so(GOMP_parallel_start+0x115) [0x7f082b9d9a35]
     [bt] (4) /home/ubuntu/anaconda3/lib/python3.7/site-packages/mxnet/libmxnet.so(+0x2817760) [0x7f07efbeb760]
     [bt] (5) /home/ubuntu/anaconda3/lib/python3.7/site-packages/mxnet/libmxnet.so(+0x281cd8d) [0x7f07efbf0d8d]
     [bt] (6) /home/ubuntu/anaconda3/lib/python3.7/site-packages/mxnet/libmxnet.so(mxnet::NDArray::SyncCopyFromCPU(void const*, unsigned long) const+0x27c) [0x7f07efb7c5ac]
     [bt] (7) /home/ubuntu/anaconda3/lib/python3.7/site-packages/mxnet/libmxnet.so(MXNDArraySyncCopyFromCPU+0x2b) [0x7f07ef8f890b]
     [bt] (8) /home/ubuntu/anaconda3/lib/python3.7/lib-dynload/../../libffi.so.6(ffi_call_unix64+0x4c) [0x7f082c4a5ec0]
   '''
   
   The worst of all, there isn't any useful information from the message, except "segment fault". Hope this problem could be solved. But I'm moving on by launching a new server instance now.

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