## Issue

Based on the Tensorflow Documentation, one can add label smoothing to categorical_crossentropy by adding label_smoothing argument. My question is what about sparse categorical crossentropy loss. There is no label_smoothing argument for this loss function.

## Solution

It’s easy to write your own loss function:

```
from tensorflow.keras.losses import categorical_crossentropy
def scce_with_ls(y, y_hat):
y = tf.one_hot(tf.cast(y, tf.int32), n_classes)
return categorical_crossentropy(y, y_hat, label_smoothing = 0.1)
```

Answered By – Björn Lindqvist

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