This package contains implementations standalone, commonly reusable PyTorch nn.Module
s. To
install it run
pip install mi-module-zoo
Documentation of the library is found at https://microsoft.github.io/mi-module-zoo/.
This library is maintained by the Machine Intelligence group in Microsoft Research.
A list of the modules follows, for detailed documentation, please check the docstring of each module.
mi_model_zoo.mlp.construct_mlp()
A function that generates an nn.Sequential
for ami_model_zoo.settransformer.SetTransformer
The Set Transformer models.mi_model_zoo.settransformer.ISAB
An Inducing-point Self-Attention Block from the Set Transformer paper.mi_model_zoo.RelationalMultiheadAttention
The relational multi-head attention variants,mi_model_zoo.relationaltransformerlayers.RelationalTransformerEncoderLayer
A relationalmi_model_zoo.relationaltransformerlayers.RelationalTransformerDecoderLayer
A relationalmi_model_zoo.utils.randomutils.set_seed()
Set the seed across Python, NumPy, and PyTorch (CPU+CUDA).mi_model_zoo.utils.activationutils.get_activation_fn()
Get an activation function by name.To develop in this repository, clone the repository, install pre-commit, and run
pre-commit install
To deploy a package to PyPI, create a release on GitHub with a git tag of the form vX.Y.Z
.
A GitHub Action will automatically build and push the package to PyPI.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.
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