[GitHub] [incubator-mxnet] eric-haibin-lin opened a new issue #14888: Memory usage estimator

[GitBox <gi...@apache.org>]

eric-haibin-lin opened a new issue #14888: Memory usage estimator
URL: https://github.com/apache/incubator-mxnet/issues/14888
 
 
   GPU memory is limited. It would be great to have an utility function to estimate the memory usage of training a model given the shape of the input. Currently, the only way is to run the model with different hidden_size and batch_size (trial and error). MXNet could provide an API that makes this process automatic so that it's easier for the user. @Roshrini @pinaraws  @cgraywang @yifeim feel free to add additional contexts
   
   For example, there is a 3rdparty library that prints the theoretical memory consumption of a pytorch model's forward/backward intermediate data entries, weights and gradients. https://github.com/jacobkimmel/pytorch_modelsize 
   
   In MXNet we can record the memory planning of a model and report the memory usage given input shapes. This does not include the temporary memory requested at runtime (e.g. by MKLDNN/CUDNN). If reporting planned memory usage not accurate enough, we can simply run the trials and return the actual peak memory usage at runtime. 

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