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<button value="stable" default="">See Stable</button> <button value="nightly">See Nightly</button>

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/losses/losses.py#L2307-L2371) |

Computes the sparse categorical crossentropy loss.

#### View aliases


**Main aliases**

[`tf.keras.metrics.sparse_categorical_crossentropy`](https://www.tensorflow.org/api_docs/python/tf/keras/losses/sparse_categorical_crossentropy.md.txt)

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```python
tf.keras.losses.sparse_categorical_crossentropy(
    y_true, y_pred, from_logits=False, ignore_class=None, axis=-1
)
```

### Used in the notebooks

| Used in the guide | Used in the tutorials |
|---|---|
| - [Use TPUs](https://www.tensorflow.org/guide/tpu.md.txt) | - [Using DTensors with Keras](https://www.tensorflow.org/tutorials/distribute/dtensor_keras_tutorial.md.txt) - [Introduction to the TensorFlow Models NLP library](https://www.tensorflow.org/tfmodels/nlp.md.txt) |

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| ## Args ||
|---|---|
| `y_true` | Ground truth values. |
| `y_pred` | The predicted values. |
| `from_logits` | Whether `y_pred` is expected to be a logits tensor. By default, we assume that `y_pred` encodes a probability distribution. |
| `ignore_class` | Optional integer. The ID of a class to be ignored during loss computation. This is useful, for example, in segmentation problems featuring a "void" class (commonly -1 or 255) in segmentation maps. By default (`ignore_class=None`), all classes are considered. |
| `axis` | Defaults to `-1`. The dimension along which the entropy is computed. |

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| ## Returns ||
|---|---|
| Sparse categorical crossentropy loss value. ||

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#### Examples:

```python
y_true = [1, 2]
y_pred = [[0.05, 0.95, 0], [0.1, 0.8, 0.1]]
loss = keras.losses.sparse_categorical_crossentropy(y_true, y_pred)
assert loss.shape == (2,)
loss
array([0.0513, 2.303], dtype=float32)
```