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[Solved] PyTorch RuntimeError: DataLoader worker (pid(s) 15332) exited unexpectedly

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error PyTorch RuntimeError: DataLoader worker (pid(s) 15332) exited unexpectedly in Python. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

How PyTorch RuntimeError: DataLoader worker (pid(s) 15332) exited unexpectedly Error Occurs?

Today I get the following error PyTorch RuntimeError: DataLoader worker (pid(s) 15332) exited unexpectedly in Python.

How To Solve PyTorch RuntimeError: DataLoader worker (pid(s) 15332) exited unexpectedly Error ?

  1. How To Solve PyTorch RuntimeError: DataLoader worker (pid(s) 15332) exited unexpectedly Error ?

    To Solve PyTorch RuntimeError: DataLoader worker (pid(s) 15332) exited unexpectedly Error Restart your system for the GPU to regain its memory. Save all the work and restart your System.

  2. PyTorch RuntimeError: DataLoader worker (pid(s) 15332) exited unexpectedly

    To Solve PyTorch RuntimeError: DataLoader worker (pid(s) 15332) exited unexpectedly Error Restart your system for the GPU to regain its memory. Save all the work and restart your System.

Solution 1

There is no “complete” solve for GPU out of memory errors, but there are quite a few things you can do to relieve the memory demand. Also, make sure that you are not passing the trainset and testset to the GPU at the same time!

  1. Decrease batch size to 1
  2. Decrease the dimensionality of the fully-connected layers (they are the most memory-intensive)
  3. (Image data) Apply centre cropping
  4. (Image data) Transform RGB data to greyscale
  5. (Text data) Truncate input at n chars (which probably won’t help that much)

Alternatively, you can try running on Google Colaboratory (12 hour usage limit on K80 GPU) and Next Journal, both of which provide up to 12GB for use, free of charge. Worst case scenario, you might have to conduct training on your CPU. Hope this helps!

Solution 2

Restart your system for the GPU to regain its memory. Save all the work and restart your System.

Summery

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

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