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I am getting following error while trying to use tensorflow with parallel processing. I saw multiple answers like Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2 but, is not related to parallel processing. I tried and is not working in my case.

here is the piece of code I used to do parallel processing

from multiprocessing import  Pool
feature_dic = {}
if __name__ == '__main__':
    max_number_process = 30
    p = Pool(max_number_process)
    fet, result = p.map(get_feature_vector_average_matrix, list_compounds)
    print(result)
    p.close()
    p.join()

If I call the function get_feature_vector_average_matrix, without parallel processing it give me the desired result and no warnings. Could you please help me on this. I am using anaconda. Thanks in advance.

Error

Using TensorFlow backend.
2019-06-10 10:53:49.553787: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2019-06-10 10:53:49.563624: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2394415000 Hz
2019-06-10 10:53:49.567835: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x559fa6cf2660 executing computations on platform Host. Devices:
2019-06-10 10:53:49.567876: I tensorflow/compiler/xla/service/service.cc:158]   StreamExecutor device (0): <undefined>, <undefined>
OMP: Info #212: KMP_AFFINITY: decoding x2APIC ids.
OMP: Info #210: KMP_AFFINITY: Affinity capable, using global cpuid leaf 11 info
OMP: Info #154: KMP_AFFINITY: Initial OS proc set respected: 0-39
OMP: Info #156: KMP_AFFINITY: 40 available OS procs
OMP: Info #157: KMP_AFFINITY: Uniform topology
OMP: Info #179: KMP_AFFINITY: 2 packages x 10 cores/pkg x 2 threads/core (20 total cores)
OMP: Info #214: KMP_AFFINITY: OS proc to physical thread map:
OMP: Info #171: KMP_AFFINITY: OS proc 0 maps to package 0 core 0 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 20 maps to package 0 core 0 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 1 maps to package 0 core 1 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 21 maps to package 0 core 1 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 2 maps to package 0 core 2 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 22 maps to package 0 core 2 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 3 maps to package 0 core 3 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 23 maps to package 0 core 3 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 4 maps to package 0 core 4 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 24 maps to package 0 core 4 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 5 maps to package 0 core 8 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 25 maps to package 0 core 8 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 6 maps to package 0 core 9 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 26 maps to package 0 core 9 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 7 maps to package 0 core 10 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 27 maps to package 0 core 10 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 8 maps to package 0 core 11 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 28 maps to package 0 core 11 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 9 maps to package 0 core 12 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 29 maps to package 0 core 12 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 10 maps to package 1 core 0 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 30 maps to package 1 core 0 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 11 maps to package 1 core 1 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 31 maps to package 1 core 1 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 12 maps to package 1 core 2 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 32 maps to package 1 core 2 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 13 maps to package 1 core 3 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 33 maps to package 1 core 3 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 14 maps to package 1 core 4 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 34 maps to package 1 core 4 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 15 maps to package 1 core 8 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 35 maps to package 1 core 8 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 16 maps to package 1 core 9 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 36 maps to package 1 core 9 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 17 maps to package 1 core 10 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 37 maps to package 1 core 10 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 18 maps to package 1 core 11 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 38 maps to package 1 core 11 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 19 maps to package 1 core 12 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 39 maps to package 1 core 12 thread 1 
OMP: Info #250: KMP_AFFINITY: pid 11661 tid 11661 thread 0 bound to OS proc set 0
2019-06-10 10:53:49.586954: I tensorflow/core/common_runtime/process_util.cc:71] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.
OMP: Info #250: KMP_AFFINITY: pid 11794 tid 11794 thread 0 bound to OS proc set 0
OMP: Info #250: KMP_AFFINITY: pid 11796 tid 11796 thread 0 bound to OS proc set 0
OMP: Info #250: KMP_AFFINITY: pid 11795 tid 11795 thread 0 bound to OS proc set 0

UPDATES: Before I did not get any output. I tried to install tensorflow from source as explained in the link but did not help. Finally, to get the output I imported tensorflow inside the working function and run different session for each process and I get the output. But the warning is still there, but is working.

hemanta
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  • It's not an error, it's an *info*. – deceze Jun 10 '19 at 15:10
  • @deceze: But I do not see any output and the console never close. It shows running. – hemanta Jun 10 '19 at 15:11
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    Perhaps it never finishes? Either way, the meaning of that particular line is well explained in the question you link to, and is entirely irrelevant (unless you want to optimise for more performance). If your program isn't finishing, that's a different question. Concentrate on that instead and [edit] your question so we have all the info we need to answer that part. – deceze Jun 10 '19 at 15:13

0 Answers0