`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.