# helia_edge.layers.preprocessing.layer_normalization

## Layer Normalization Layer API

This module provides classes to build layer normalization layers.

**Classes**

| Name | Description |
| --- | --- |
| `LayerNormalization1D` | Layer normalization for 1D data |
| `LayerNormalization2D` | Layer normalization for 2D data |

## helia_edge.layers.preprocessing.layer_normalization.LayerNormalization1D

`class` · `python`

```python
LayerNormalization1D(epsilon: float = 1e-06, name=None, **kwargs={})
```

Apply Layer Normalization to the input.



Base class: [BaseAugmentation1D](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation1D).

Inherited from [BaseAugmentation](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation): [augment_masks()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.augment_masks), [augment_sample()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.augment_sample), [augment_targets()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.augment_targets), [batch_augment()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.batch_augment), [call()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.call), [get_random_transformations()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.get_random_transformations).

**Parameters**

| Name | Type | Default | Description |
| --- | --- | --- | --- |
| epsilon | float | 1e-06 | Small value to avoid division by zero. |

Source: `helia_edge/layers/preprocessing/layer_normalization.py:18`

### helia_edge.layers.preprocessing.layer_normalization.LayerNormalization1D.training_only

`attribute` · `python`

```python
training_only = False
```

Source: `helia_edge/layers/preprocessing/layer_normalization.py:20`

### helia_edge.layers.preprocessing.layer_normalization.LayerNormalization1D.epsilon

`attribute` · `python`

```python
epsilon = epsilon
```

Source: `helia_edge/layers/preprocessing/layer_normalization.py:34`

### helia_edge.layers.preprocessing.layer_normalization.LayerNormalization1D.augment_samples

`method` · `python`

```python
augment_samples(inputs) -> keras.KerasTensor
```

Augment a batch of samples during training.

Source: `helia_edge/layers/preprocessing/layer_normalization.py:36`

### helia_edge.layers.preprocessing.layer_normalization.LayerNormalization1D.get_config

`method` · `python`

```python
get_config()
```

Source: `helia_edge/layers/preprocessing/layer_normalization.py:47`

## helia_edge.layers.preprocessing.layer_normalization.LayerNormalization2D

`class` · `python`

```python
LayerNormalization2D(epsilon: float = 1e-06, name=None, **kwargs={})
```

Apply Layer Normalization to the input.



Base class: [BaseAugmentation2D](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation2D).

Inherited from [BaseAugmentation](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation): [augment_masks()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.augment_masks), [augment_sample()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.augment_sample), [augment_targets()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.augment_targets), [batch_augment()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.batch_augment), [call()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.call), [get_random_transformations()](/helia-edge/reference/api/helia_edge/layers/preprocessing/base_augmentation/#helia_edge.layers.preprocessing.base_augmentation.BaseAugmentation.get_random_transformations).

**Parameters**

| Name | Type | Default | Description |
| --- | --- | --- | --- |
| epsilon | float | 1e-06 | Small value to avoid division by zero. |

Source: `helia_edge/layers/preprocessing/layer_normalization.py:51`

### helia_edge.layers.preprocessing.layer_normalization.LayerNormalization2D.training_only

`attribute` · `python`

```python
training_only = False
```

Source: `helia_edge/layers/preprocessing/layer_normalization.py:53`

### helia_edge.layers.preprocessing.layer_normalization.LayerNormalization2D.epsilon

`attribute` · `python`

```python
epsilon = epsilon
```

Source: `helia_edge/layers/preprocessing/layer_normalization.py:67`

### helia_edge.layers.preprocessing.layer_normalization.LayerNormalization2D.augment_samples

`method` · `python`

```python
augment_samples(inputs) -> keras.KerasTensor
```

Augment a batch of samples during training.

Source: `helia_edge/layers/preprocessing/layer_normalization.py:69`

### helia_edge.layers.preprocessing.layer_normalization.LayerNormalization2D.get_config

`method` · `python`

```python
get_config()
```

Source: `helia_edge/layers/preprocessing/layer_normalization.py:80`