title: Stop TensorFlow from printing warning message
body: <p>I am working on a Kaggle notebook and whenever I run a cell that references the TensorFlow module at all, it prints out a huge warning about some sort of settings but still works. I looked up how to suppress warnings from TensorFlow, and everything I found said to do the following:</p>
  <pre class="lang-py prettyprint-override"><code>import os
  os.environ[&quot;TF_CPP_MIN_LOG_LEVEL&quot;] = &quot;2&quot; # Or &quot;3&quot;, either one should work and I've tried both
  </code></pre>
  <p>I have tried putting this both before and after importing TensorFlow but to no avail. The message still prints out. This is the message I am getting:</p>
  <pre><code>User settings:
  
     KMP_AFFINITY=granularity=fine,verbose,compact,1,0
     KMP_BLOCKTIME=0
     KMP_SETTINGS=1
     KMP_WARNINGS=0
  
  Effective settings:
  
     KMP_ABORT_DELAY=0
     KMP_ADAPTIVE_LOCK_PROPS='1,1024'
     KMP_ALIGN_ALLOC=64
     KMP_ALL_THREADPRIVATE=128
     KMP_ATOMIC_MODE=2
     KMP_BLOCKTIME=0
     KMP_CPUINFO_FILE: value is not defined
     KMP_DETERMINISTIC_REDUCTION=false
     KMP_DEVICE_THREAD_LIMIT=2147483647
     KMP_DISP_NUM_BUFFERS=7
     KMP_DUPLICATE_LIB_OK=false
     KMP_ENABLE_TASK_THROTTLING=true
     KMP_FORCE_REDUCTION: value is not defined
     KMP_FOREIGN_THREADS_THREADPRIVATE=true
     KMP_FORKJOIN_BARRIER='2,2'
     KMP_FORKJOIN_BARRIER_PATTERN='hyper,hyper'
     KMP_GTID_MODE=3
     KMP_HANDLE_SIGNALS=false
     KMP_HOT_TEAMS_MAX_LEVEL=1
     KMP_HOT_TEAMS_MODE=0
     KMP_INIT_AT_FORK=true
     KMP_LIBRARY=throughput
     KMP_LOCK_KIND=queuing
     KMP_MALLOC_POOL_INCR=1M
     KMP_NUM_LOCKS_IN_BLOCK=1
     KMP_PLAIN_BARRIER='2,2'
     KMP_PLAIN_BARRIER_PATTERN='hyper,hyper'
     KMP_REDUCTION_BARRIER='1,1'
     KMP_REDUCTION_BARRIER_PATTERN='hyper,hyper'
     KMP_SCHEDULE='static,balanced;guided,iterative'
     KMP_SETTINGS=true
     KMP_SPIN_BACKOFF_PARAMS='4096,100'
     KMP_STACKOFFSET=64
     KMP_STACKPAD=0
     KMP_STACKSIZE=8M
     KMP_STORAGE_MAP=false
     KMP_TASKING=2
     KMP_TASKLOOP_MIN_TASKS=0
     KMP_TASK_STEALING_CONSTRAINT=1
     KMP_TEAMS_THREAD_LIMIT=4
     KMP_TOPOLOGY_METHOD=all
     KMP_USE_YIELD=1
     KMP_VERSION=false
     KMP_WARNINGS=false
     OMP_AFFINITY_FORMAT='OMP: pid %P tid %i thread %n bound to OS proc set {%A}'
     OMP_ALLOCATOR=omp_default_mem_alloc
     OMP_CANCELLATION=false
     OMP_DEFAULT_DEVICE=0
     OMP_DISPLAY_AFFINITY=false
     OMP_DISPLAY_ENV=false
     OMP_DYNAMIC=false
     OMP_MAX_ACTIVE_LEVELS=1
     OMP_MAX_TASK_PRIORITY=0
     OMP_NESTED: deprecated; max-active-levels-var=1
     OMP_NUM_THREADS: value is not defined
     OMP_PLACES: value is not defined
     OMP_PROC_BIND='intel'
     OMP_SCHEDULE='static'
     OMP_STACKSIZE=8M
     OMP_TARGET_OFFLOAD=DEFAULT
     OMP_THREAD_LIMIT=2147483647
     OMP_WAIT_POLICY=PASSIVE
     KMP_AFFINITY='verbose,warnings,respect,granularity=fine,compact,1,0'
  </code></pre>
  <p>Is there any way I can stop this from printing?</p>
  <p>EDIT: Code to reproduce this message:</p>
  <pre class="lang-py prettyprint-override"><code>import tensorflow as tf
  tf.constant(())
  </code></pre>
  <p>EDIT: Output of <code>env</code>:</p>
  <pre><code>{'SHELL': '/bin/bash',
   'KMP_WARNINGS': '0',
   'DL_ANACONDA_HOME': '/opt/conda',
   'KAGGLE_DATA_PROXY_TOKEN': '&lt;hidden&gt;',
   'KAGGLE_URL_BASE': 'https://www.kaggle.com',
   'KAGGLE_KERNEL_INTEGRATIONS': '',
   'CONTAINER_NAME': 'tf2-cpu/2-6',
   'PWD': '/kaggle/working',
   'TESSERACT_PATH': '/usr/bin/tesseract',
   'TENSORFLOW_VERSION': '2.6.0',
   'HOME': '/root',
   'LANG': 'C.UTF-8',
   'KMP_SETTINGS': '1',
   'JAX_VERSION': '0.2.19',
   'CONTAINER_URL': 'gcr.io/deeplearning-platform-release/tf-cpu.2-6:nightly-2021-11-17',
   'ANACONDA_PYTHON_VERSION': '3.7',
   'PYTHONPATH': '/kaggle/lib/kagglegym:/kaggle/lib:/kaggle/input/tensorflow-great-barrier-reef',
   'KMP_BLOCKTIME': '0',
   'KAGGLE_DATA_PROXY_PROJECT': 'kaggle-161607',
   'KAGGLE_USER_SECRETS_TOKEN': '&lt;hidden&gt;',
   'SHLVL': '1',
   'KAGGLE_KERNEL_RUN_TYPE': 'Interactive',
   'PROJ_LIB': '/opt/conda/share/proj',
   'MPLBACKEND': 'agg',
   'LD_LIBRARY_PATH': '/usr/local/cuda/lib64:/usr/local/cuda/lib:/usr/local/lib/x86_64-linux-gnu:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:',
   'KMP_AFFINITY': 'granularity=fine,verbose,compact,1,0',
   'MKL_THREADING_LAYER': 'GNU',
   'LC_ALL': 'C.UTF-8',
   'PATH': '/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin',
   'PYTHONUSERBASE': '/root/.local',
   'KAGGLE_DATA_PROXY_URL': 'https://dp.kaggle.net',
   '_': '/opt/conda/bin/jupyter',
   'GIT_PYTHON_REFRESH': 'quiet',
   'PYDEVD_USE_FRAME_EVAL': 'NO',
   'JPY_PARENT_PID': '9',
   'TERM': 'xterm-color',
   'CLICOLOR': '1',
   'PAGER': 'cat',
   'GIT_PAGER': 'cat',
   'TF_CPP_MIN_LOG_LEVEL': '2',
   'TF2_BEHAVIOR': '1'}
  </code></pre>