pytorch-lightning/pytorch_lightning/metrics/__init__.py

"""
Metrics
=======

Metrics are generally used to monitor model performance.

The following package aims to provide the most convenient ones as well
as a structure to implement your custom metrics for all the fancy research
you want to do.

For native PyTorch implementations of metrics, it is recommended to use
the :class:`TensorMetric` which handles automated DDP syncing and conversions
to tensors for all inputs and outputs.

If your metrics implementation works on numpy, just use the
:class:`NumpyMetric`, which handles the automated conversion of
inputs to and outputs from numpy as well as automated ddp syncing.

.. warning:: Employing numpy in your metric calculation might slow
    down your training substantially, since every metric computation
    requires a GPU sync to convert tensors to numpy.


"""