`R/backend.R`

`k_normalize_batch_in_training.Rd`

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

k_normalize_batch_in_training(x, gamma, beta, reduction_axes, epsilon = 0.001)

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. |

A list length of 3, `(normalized_tensor, mean, variance)`

.

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.