torchfunc¶

torchfunc is PyTorch oriented library with a goal to help you with:

Improving and analysing performance of your neural network
Record/analyse internal state of torch.nn.Module as data passes through it
Do the above based on external conditions (using single Callable to specify it)
Day-to-day neural network related duties (model size, seeding, performance measurements etc.)
Get information about your host operating system, CUDA devices and others

See related projects for other helpful libraries revolving around PyTorch.

Modules¶

Installation¶

Following installation methods are available:

pip:¶

To install latest release:

pip install --user torchfunc

To install nightly version:

pip install --user torchfunc-nightly

Docker:¶

Various torchfunc images are available both CPU and GPU-enabled. You can find them in Docker Cloud at szymonmaszke/torchfunc

CPU¶

CPU image is based on ubuntu:18.04 and official release can be pulled with:

docker pull szymonmaszke/torchfunc:18.04

For nightly release:

docker pull szymonmaszke/torchfunc:nightly_18.04

This image is significantly lighter due to lack of GPU support.

GPU¶

All images are based on nvidia/cuda Docker image. Each has corresponding CUDA version tag ( 10.1, 10 and 9.2) CUDNN7 support and base image ( ubuntu:18.04 ).

Following images are available:

10.1-cudnn7-runtime-ubuntu18.04
10.1-runtime-ubuntu18.04
10.0-cudnn7-runtime-ubuntu18.04
10.0-runtime-ubuntu18.04
9.2-cudnn7-runtime-ubuntu18.04
9.2-runtime-ubuntu18.04

Example pull:

docker pull szymonmaszke/torchfunc:10.1-cudnn7-runtime-ubuntu18.04

You can use nightly builds as well, just prefix the tag with nightly_, for example like this:

docker pull szymonmaszke/torchfunc:nightly_10.1-cudnn7-runtime-ubuntu18.04

conda:¶

TO BE ADDED

conda install -c conda-forge torchfunc