# tf.keras.backend.normalize_batch_in_training

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|---|---|
| [![](https://www.tensorflow.org/images/tf_logo_32px.png) TensorFlow 1 version](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/backend/normalize_batch_in_training) | [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.1.0/tensorflow/python/keras/backend.py#L2558-L2585) |

Computes mean and std for batch then apply batch_normalization on batch.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.keras.backend.normalize_batch_in_training`](https://www.tensorflow.org/api_docs/python/tf/keras/backend/normalize_batch_in_training)

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    tf.keras.backend.normalize_batch_in_training(
        x, gamma, beta, reduction_axes, epsilon=0.001
    )

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| ## Arguments ||
|---|---|
| `x` | Input tensor or variable. |
| `gamma` | Tensor by which to scale the input. |
| `beta` | Tensor with which to center the input. |
| `reduction_axes` | iterable of integers, axes over which to normalize. |
| `epsilon` | Fuzz factor. |

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| ## Returns ||
|---|---|
| A tuple length of 3, `(normalized_tensor, mean, variance)`. ||

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