title: Weird output when using TensorFlow backend on Keras (OMP: Info #xx KMP_AFFINITY)
body: <p>Im using Keras with a TensorFlow backend to train a neural networks model. It is a simple model (from a tutorial) and everything works fine. Model predicts the way it should. Only tensorflow seems to be outputting information, and I don't know if I can safely ignore it/what it means. Can somebody explain me what the following output tells us? Especially all the lines which start with <code>OMP</code> are unclear to me. The deprecation warning does not really worry me.</p>
  
  <pre><code>Using TensorFlow backend.
  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: 0-7
  OMP: Info #156: KMP_AFFINITY: 8 available OS procs
  OMP: Info #157: KMP_AFFINITY: Uniform topology
  OMP: Info #179: KMP_AFFINITY: 1 packages x 4 cores/pkg x 2 threads/core (4 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 1 maps to package 0 core 0 thread 1 
  OMP: Info #171: KMP_AFFINITY: OS proc 2 maps to package 0 core 1 thread 0 
  OMP: Info #171: KMP_AFFINITY: OS proc 3 maps to package 0 core 1 thread 1 
  OMP: Info #171: KMP_AFFINITY: OS proc 4 maps to package 0 core 2 thread 0 
  OMP: Info #171: KMP_AFFINITY: OS proc 5 maps to package 0 core 2 thread 1 
  OMP: Info #171: KMP_AFFINITY: OS proc 6 maps to package 0 core 3 thread 0 
  OMP: Info #171: KMP_AFFINITY: OS proc 7 maps to package 0 core 3 thread 1 
  OMP: Info #250: KMP_AFFINITY: pid 14400 tid 5252 thread 0 bound to OS proc set 0
  WARNING: Logging before flag parsing goes to stderr.
  W0820 14:05:56.256548  5252 deprecation.py:323] From C:\Users\Gebruiker\Anaconda3\envs\Anaconda3.7\lib\site-packages\tensorflow\python\ops\nn_impl.py:180: add_dispatch_support.&lt;locals&gt;.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
  Instructions for updating:
  Use tf.where in 2.0, which has the same broadcast rule as np.where
  2019-08-20 14:05:56.449349: I tensorflow/core/platform/cpu_feature_guard.cc:145] This TensorFlow binary is optimized with Intel(R) MKL-DNN to use the following CPU instructions in performance critical operations:  AVX AVX2
  To enable them in non-MKL-DNN operations, rebuild TensorFlow with the appropriate compiler flags.
  2019-08-20 14:05:56.451182: I tensorflow/core/common_runtime/process_util.cc:115] Creating new thread pool with default inter op setting: 8. Tune using inter_op_parallelism_threads for best performance.
  OMP: Info #250: KMP_AFFINITY: pid 14400 tid 13256 thread 1 bound to OS proc set 2
  OMP: Info #250: KMP_AFFINITY: pid 14400 tid 5064 thread 2 bound to OS proc set 4
  OMP: Info #250: KMP_AFFINITY: pid 14400 tid 8904 thread 3 bound to OS proc set 6
  OMP: Info #250: KMP_AFFINITY: pid 14400 tid 9408 thread 4 bound to OS proc set 1
  OMP: Info #250: KMP_AFFINITY: pid 14400 tid 14360 thread 5 bound to OS proc set 3
  OMP: Info #250: KMP_AFFINITY: pid 14400 tid 14616 thread 6 bound to OS proc set 5
  OMP: Info #250: KMP_AFFINITY: pid 14400 tid 2692 thread 7 bound to OS proc set 7
  OMP: Info #250: KMP_AFFINITY: pid 14400 tid 14172 thread 8 bound to OS proc set 0
  </code></pre>