Error #15: Initializing libiomp5.dylib, but found libiomp5.dylib already initialized

Question

Getting the error message when using matplotlib:

Error #15: Initializing libiomp5.dylib, but found libiomp5.dylib already initialized OMP: Hin

Answer 1

So, for those of you getting this same issue with lightgbm, I found in the documentation that you can

1. pip uninstall lightgbm
2. pip install lightgbm
3. Run the following in anaconda environmnet (if you're running Conda)

ln -sf `ls -d "$(brew --cellar libomp)"/*/lib`/* $CONDA_PREFIX/lib

These three things worked for me.

Answer 2

I had the same issue in a conda environment where TensorFlow was installed. After doing

• pip uninstall tensorflow
• pip install tensorflow

the problem was gone.

Answer 3

conda install --revision 0 doesn't solve UnsatisfiableError: The following specifications... for me. So I manually install nomkl and remove mkl and mil-service in Anaconda-Navigator environment, and it works great for me!

Answer 4

This seems to be a MacOS problem. Do the following to solve the issue:

import os

os.environ['KMP_DUPLICATE_LIB_OK']='True'

Answer found at: https://github.com/dmlc/xgboost/issues/1715

Be aware of potential side-effects:

"but that may cause crashes or silently produce incorrect results."

Answer 5

Check if there's an update for the mkl package in your env (anaconda).

I was able to solve my case simply by updating mkl.

conda install -c intel mkl

(macOS Catalina 10.15.5)

Answer 6

Had same issue in OSX when updating tensoflow to 1.13 using conda.

• Solution 1: /gcamargo worked but 3x slower per training epoch.
• Solution 2: /sjcoding worked and removed serious warining but also 3x slower in training.
• Solution 3: that restored performance was: Install pip in new conda env and use pip to install tensorflow. Using conda-forge also worked but version of tf is old.

Apparently the new Intel-MKL optimizations in Anaconda are broken for OSX tensorflow.