layer_norm(x, normalized_idxs, epsilon=None, gamma=None, beta=None, new_std=None)¶
Applies Layer Normalization over a mini-batch of inputs
x (array) – Input array
normalized_idxs (int or sequence of ints) – Indices to apply the normalization to.
epsilon (float, optional) – small constant to add to the denominator, use global ivy._MIN_BASE by default.
gamma (array, optional) – Learnable gamma variables for post-multiplication, default is None.
beta (array, optional) – Learnable beta variables for post-addition, default is None.
new_std (float, optional) – The standard deviation of the new normalized values. Default is 1.
The layer after applying layer normalization.