This TensorFlow binary is optimized with Intel(R) MKL-DNN to use the following CPU instructions in performance critical

Question

I ma trying to install tensorflow on Ubuntu and I am getting this message :

(base) k@k-1005:~/Documents/ClassificationTexte/src$ python tester.py 
Using TensorFlow backend.


RUN: 1
  1.1. Training the classifier...
LABELS: {'negative', 'neutral', 'positive'}
2019-12-10 11:58:13.428875: 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:  SSE4.1 SSE4.2 AVX AVX2 FMA
To enable them in non-MKL-DNN operations, rebuild TensorFlow with the appropriate compiler flags.
2019-12-10 11:58:13.432727: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3190585000 Hz
2019-12-10 11:58:13.433041: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5591c387b750 executing computations on platform Host. Devices:
2019-12-10 11:58:13.433098: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): Host, Default Version
2019-12-10 11:58:13.433182: I tensorflow/core/common_runtime/process_util.cc:115] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.
Model: "model_1"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_1 (InputLayer)         (None, 8000)              0         
_________________________________________________________________
dense_1 (Dense)              (None, 3)                 24003     

But the script works and display the accuracy but this part above show before the runs. Do you have any idea , I install tensorflow on anaconda :

Answer 1

In case you are not interested seeing those errors use this before running your script

export TF_CPP_MIN_LOG_LEVEL=2

or

import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

inside your script.

Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

Update: A little cleaner way inside your code: tf.get_logger().setLevel('ERROR')

Answer 2

The above warning is thrown because TensorFlow library was originally compiled on different architecture machine and is not optimized for your particular architecture. Which means that it will continue to function, but you won't be getting max performance out of the library.

To get the max performance on your machine, you need to build TensorFlow on your machine.

Refer to the official documentation for the steps for building from source.

Official Docs: https://www.tensorflow.org/install/source