25 lines
819 B
Python
25 lines
819 B
Python
"""
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Metrics
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=======
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Metrics are generally used to monitor model performance.
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The following package aims to provide the most convenient ones as well
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as a structure to implement your custom metrics for all the fancy research
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you want to do.
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For native PyTorch implementations of metrics, it is recommended to use
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the :class:`TensorMetric` which handles automated DDP syncing and conversions
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to tensors for all inputs and outputs.
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If your metrics implementation works on numpy, just use the
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:class:`NumpyMetric`, which handles the automated conversion of
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inputs to and outputs from numpy as well as automated ddp syncing.
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.. warning:: Employing numpy in your metric calculation might slow
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down your training substantially, since every metric computation
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requires a GPU sync to convert tensors to numpy.
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"""
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