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On the recordRead 11 Oct 202624 facts
TorchMetrics
Plans and prices
TorchMetrics
Free
100+ PyTorch metrics; Apache 2.0 license
Read 11 Oct 2026 · github.com
On the record
- Batch accumulation
- Metrics can accumulate results across batches and compute an aggregate value.lightning.ai · read 11 Oct 2026
- Bayesian analysis
- Nolightning.ai · read 23 Sep 2026
- Community support
- The project repository directs users with questions to its Discord community.github.com · read 11 Oct 2026
- Compatibility limit
- The documentation says TorchMetrics supports the latest two major PyTorch Lightning versions and recommends keeping both frameworks up to date.lightning.ai · read 11 Oct 2026
- Custom metrics
- Users can create custom metrics by subclassing Metric and implementing update() and compute().lightning.ai · read 11 Oct 2026
- Distributed training
- Module metrics support automatic accumulation across batches and synchronization across devices for distributed training.lightning.ai · read 11 Oct 2026
- Installation
- The project documents installation with pip, conda, uv, or directly from its source repository.github.com · read 11 Oct 2026
- Interfaces
- TorchMetrics provides module-based metrics and functional metrics that take tensors as input and return metric values as tensors.github.com · read 11 Oct 2026
- License
- The project repository states that TorchMetrics is licensed under Apache 2.0.github.com · read 11 Oct 2026
- Lightning integration
- When used with PyTorch Lightning, metrics can be logged with self.log and are automatically placed on the correct device when properly defined inside a LightningModule.lightning.ai · read 11 Oct 2026
- Metric collections
- MetricCollection wraps multiple metrics in one callable metric class.lightning.ai · read 11 Oct 2026
- Metric coverage
- The project lists more than 100 metrics across audio, classification, detection, information retrieval, image, multimodal, nominal, regression, segmentation, and text domains.github.com · read 11 Oct 2026
- Optional dependencies
- Specialized audio, image, and text metrics may require extra dependencies, which can be installed with package extras.github.com · read 11 Oct 2026
- Plotting
- Nearly all modular metrics support plotting through the plot method when the visualization dependencies are installed.github.com · read 11 Oct 2026
- Purpose
- TorchMetrics is a collection of more than 100 PyTorch metrics implementations with an API for creating custom metrics.lightning.ai · read 11 Oct 2026
- PyTorch integration
- TorchMetrics can be used directly with PyTorch models independently of PyTorch Lightning.lightning.ai · read 11 Oct 2026
- PyTorch Lightning integration
- When metrics are properly defined inside a LightningModule, Lightning can place them on the module’s device and log them with self.log or self.log_dict.lightning.ai · read 11 Oct 2026
- Regression models
- Nolightning.ai · read 23 Sep 2026
