# k_batch_dot

## Batchwise dot product.

## Description

`batch_dot`

is used to compute dot product of `x`

and `y`

when `x`

and `y`

are data in batch, i.e. in a shape of `(batch_size)`

. `batch_dot`

results in a tensor or variable with less dimensions than the input. If the number of dimensions is reduced to 1, we use `expand_dims`

to make sure that ndim is at least 2.

## Usage

```
k_batch_dot(x, y, axes)
```

## Arguments

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

x | Keras tensor or variable with 2 more more axes. |

y | Keras tensor or variable with 2 or more axes |

axes | List of (or single) integer with target dimensions (axis indexes are 1-based). The lengths of `axes[[1]]` and `axes[[2]]` should be the same. |

## Section

## Keras Backend

This function is part of a set of Keras backend functions that enable lower level access to the core operations of the backend tensor engine (e.g. TensorFlow, CNTK, Theano, etc.). You can see a list of all available backend functions here: https://keras.rstudio.com/articles/backend.html#backend-functions.

## Value

A tensor with shape equal to the concatenation of `x`

’s shape (less the dimension that was summed over) and `y`

’s shape (less the batch dimension and the dimension that was summed over). If the final rank is 1, we reshape it to `(batch_size, 1)`

.