# layer_dot

## Layer that computes a dot product between samples in two tensors.

## Description

Layer that computes a dot product between samples in two tensors.

## Usage

```
layer_dot(inputs, ..., axes, normalize = FALSE)
```

## Arguments

Arguments | Description |
---|---|

inputs | A input tensor, or list of input tensors. Can be missing. |

… | Unnamed args are treated as additional `inputs` . Named arguments are passed on as standard layer arguments. |

axes | Integer or list of integers, axis or axes along which to take the dot product. |

normalize | Whether to L2-normalize samples along the dot product axis before taking the dot product. If set to TRUE, then the output of the dot product is the cosine proximity between the two samples. |

## Value

If `inputs`

is supplied: A tensor, the dot product of the samples from the inputs. If `inputs`

is missing, a keras layer instance is returned.

## See Also

https://www.tensorflow.org/api_docs/python/tf/keras/layers/dot

https://keras.io/api/layers/merging_layers/dot/

Other merge layers:

`layer_average()`

,`layer_concatenate()`

,`layer_maximum()`

,`layer_minimum()`

,`layer_multiply()`

,`layer_subtract()`