PyTorch-Ignite
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About
PyTorch-Ignite is a high-level library designed to facilitate training and evaluating neural networks within the PyTorch ecosystem. It offers a simple engine and event system that allows users to trigger handlers at built-in and custom events. The library supports checkpointing, early stopping, and profiling, making it flexible for various training scenarios. It is optimized for distributed training on CPUs, GPUs, and TPUs and comes with over 50 built-in metrics for easy model evaluation. Integration with popular experiment managers like Tensorboard and MLFlow enhances its usability for monitoring training processes and logging metrics. PyTorch-Ignite is designed as a community-driven open-source project, with contributions from enthusiastic developers and strong governance to ensure a thriving ecosystem.
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Task
Features
• rich ecosystem with support for multiple projects
• checkpointing and early stopping capabilities
• integration with tensorboard, mlflow, and more
• built-in metrics for model evaluation
• supports distributed training for various hardware setups
• simple event system for custom and built-in events
• high-level api for training and evaluating neural networks
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