torch-metrics
by enochkan
Metrics for model evaluation in pytorch
AI summary
Metrics library
A collection of common machine learning evaluation metrics implemented in PyTorch
- stars
- 110
- forks
- 14
- watching
- 3
Similar projects
Found by comparing what the projects do, not just their names.
Metric learning framework
A PyTorch-based framework for training and validating models that produce high-quality embeddings for computer vision and other tasks.
Evaluation metrics library
Provides implementations of various supervised machine learning evaluation metrics in multiple programming languages.
GA trainer
Trains PyTorch models using a genetic algorithm
Segmentation metrics library
A library providing an implementation of various metrics for object segmentation and saliency detection in computer vision.
Model trainer
A PyTorch model fitting library designed to simplify the process of training deep learning models.
DR framework
A PyTorch-based framework for dimensionality reduction and manifold learning
Segmentation toolkit
A toolkit for building and training semantic segmentation models using PyTorch.
Deep learning library
Provides a CUDA backend for the PyTorch deep learning framework
Batching library
A PyTorch module for dynamic batching and optimized computation on deep neural networks
PyTorch toolkit
A collection of utility functions and tools for building deep learning models with PyTorch
Pipeline Parallelism Library
A PyTorch-based library for efficient training of large neural networks using pipeline parallelism and automatic recomputation of gradients.
Model converter
A tool for converting models between Caffe and PyTorch
Model converter
Converts PyTorch models to various formats for deployment and testing in deep learning frameworks.
Metrics library
Provides a simple and efficient way to track and expose performance metrics in Go applications.
Deep Learning Wrapper
Provides Python wrappers for PyTorch and Lua, enabling developers to use PyTorch's deep learning capabilities from both languages.
