I'm running windows 10 with the following library versions:
matplotlib 3.3.3
torch 1.7.0
pandas 1.1.4
When I load from CSV a dataframe and plot its data BEFORE import torch
, I get no issues. However, if I put all of my import statements at the top of the notebook, as is tradition, I instead get a crashed kernel with the following pop up message:
The kernel for anom_detect_nn.ipynb appears to have died. It will restart automatically.
When I look at my shell, I see two error messages:
OMP: Error #15: Initializing libiomp5md.dll, but found libiomp5md.dll already initialized.
OMP: Hint This means that multiple copies of the OpenMP runtime have been linked into the program. That is dangerous, since it can degrade performance or cause incorrect results. The best thing to do is to ensure that only a single OpenMP runtime is linked into the process, eg by avoiding static linking of the OpenMP runtime in any library. As an unsafe, unsupported, undocumented workaround you can set the environment variable KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may cause crashes or silently produce incorrect results. For more information, please see http://www.intel.com/software/products/support/ .
It seems like other users on SO have experienced this before, but all of the solutions apply to MacOS users. I've tried them anyway:
conda install nomkl
pip uninstall everything
, pip install everything
KMP_DUPLICATE_LIB_OK=TRUE
Thanks to the above steps entire set-up is now a tangled mess where I can't pip install
anything successfully, and modules that are successfully installed can no longer be imported without Module not found
errors.
This is a real pain, and I'm at my wits end. I'm currently uninstalling everything Python on my system and starting over. Not a happy camper. Any solutions that are for Windows and not Mac, should this problem persist when I start over?
Same issue. This worked for me:
plt
before import torch
imshow
immediatelyimport torch
imshow
(and it doesn't crash)I don't know why, but it works...
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