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Make it clearer that losses reduce along the batch dimension #2004

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Dec 15, 2024
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Make it clearer that losses reduce along the batch dimension #2004

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3 changes: 2 additions & 1 deletion templates/api/losses/index.md
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Expand Up @@ -76,7 +76,8 @@ A loss is a callable with arguments `loss_fn(y_true, y_pred, sample_weight=None)
by the corresponding value of `sample_weight`. (Note on`dN-1`: all loss
functions reduce by 1 dimension, usually `axis=-1`.)

By default, loss functions return one scalar loss value per input sample, e.g.
By default, loss functions return one scalar loss value for each input sample
in the batch dimension, e.g.

```
>>> from keras import ops
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