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Pytorch layers for economic applications.

Project description

Pytorch Layers for Economics Applications

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Pytorch

Features

  • Exponential layer
  • Flexible multi-layer neural network with optional nonlinear last layer
  • Affine rescaling of output by an input

Development

To publish a new relase to pypi,

  1. Ensure that the CI is passing
  2. Modify setup.py to increment the minor version number, or a major version number once API stability is enforced
  3. Choose the "Releases" on the github page, then "Draft a new relase"
  4. Click on "Choose a tag" and then type a new release tag with the v followed by the version number you modified to be consistent
  5. After you choose "Publish Release" it will automatically push to pypi, and you can change compatability bounds in downstream packages as required.

Credits

This package was created with Cookiecutter and the giswqs/pypackage project template.

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