tf.keras.initializers.get

Retrieves a Keras initializer object via an identifier.

tf.keras.initializers.get(
    identifier
)

The identifier may be the string name of a initializers function or class (case-sensitively).

identifier = 'Ones'
keras.initializers.get(identifier)
<...keras.initializers.initializers.Ones...>

You can also specify config of the initializer to this function by passing dict containing class_name and config as an identifier. Also note that the class_name must map to a Initializer class.

cfg = {'class_name': 'Ones', 'config': {} }
keras.initializers.get(cfg)
<...keras.initializers.initializers.Ones...>

In the case that the identifier is a class, this method will return a new instance of the class by its constructor.

You may also pass a callable function with a signature that includes shape and dtype=None as an identifier.

fn = lambda shape, dtype=None: ops.ones(shape, dtype)
keras.initializers.get(fn)
<function <lambda> at ...>

Alternatively, you can pass a backend tensor or numpy array as the identifier to define the initializer values directly. Note that when calling the initializer, the specified shape argument must be the same as the shape of the tensor.

tensor = ops.ones(shape=(5, 5))
keras.initializers.get(tensor)
<function get.<locals>.initialize_fn at ...>

identifier A string, dict, callable function, or tensor specifying the initializer. If a string, it should be the name of an initializer. If a dict, it should contain the configuration of an initializer. Callable functions or predefined tensors are also accepted.

Initializer instance base on the input identifier.