Due to its model-level library structure, Keras may have different tensor manipulation engines that handle low-level operations, such as convolutions, tensor products, and the like. These engines are called backends. Other backends are available; we will not consider them here.
The same https://keras.io/backend/ link takes you to a wealth of keras.backend functions.
The canonical way to use the Keras backend is with the following:
from keras import backend as K
For example, here is the signature of a useful function:
K.constant(value, dtype=None, shape=None, name=None)
Here value is the value to be given to the constant, dtype is the type of the tensor that is created, shape is the shape of the tensor that is created, and name is an optional name.
An instantiation of this is as follows:
from tensorflow.keras import backend as K
const = K.constant([[42,24],[11...