[D] How to avoid CPU bottlenecking in PyTorch - training slowed by augmentations and data loading?

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  • GitHub repo pytorch-lightning

    The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

    We've noticed GPU 0 on our 3 GPU system is sometimes idle (which would explain performance differences). However its unclear to us why that may be. Similar to this issue

  • GitHub repo numexpr

    Fast numerical array expression evaluator for Python, NumPy, PyTables, pandas, bcolz and more

    Are you doing any costly chained NumPy operations in your preprocessing? E.g. max(abs(large_ary)), this produces multiple copies of your data, https://github.com/pydata/numexpr can greatly reduce time spent with such operations

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