Implementations of polygamma, lgamma, and beta functions for PyTorch

Last update: Nov 09, 2021

Overview

lgamma

Implementations of polygamma, lgamma, and beta functions for PyTorch. It's very hacky, but that's usually ok for research use.

To build, run:

./make.sh

You'll probably need to pass in the correct CUDA path to build.py, which is run inside make.sh, so modify it to instead call

python build.py --cuda-path YOUR_CUDA_PATH

Also, you'll probably need to change the architecture version/CUDA compute capability inside make.sh, so replace sm_35 with whatever your GPU supports. Feel free to open an issue if you run into another problem!

Owner

Rachit Singh

GitHub Repository

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Implementations of polygamma, lgamma, and beta functions for PyTorch

Related tags

Overview

lgamma

Owner

Rachit Singh

Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic

A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

This code is a near-infrared spectrum modeling method based on PCA and pls

FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment

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Dilated Convolution with Learnable Spacings PyTorch

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