tf.keras.layers.Maximum

Computes element-wise maximum on a list of inputs.

Inherits From: Layer, Operation

tf.keras.layers.Maximum(
    **kwargs
)

It takes as input a list of tensors, all of the same shape, and returns a single tensor (also of the same shape).

Examples:

input_shape = (2, 3, 4)
x1 = np.random.rand(*input_shape)
x2 = np.random.rand(*input_shape)
y = keras.layers.Maximum()([x1, x2])

Usage in a Keras model:

input1 = keras.layers.Input(shape=(16,))
x1 = keras.layers.Dense(8, activation='relu')(input1)
input2 = keras.layers.Input(shape=(32,))
x2 = keras.layers.Dense(8, activation='relu')(input2)
# equivalent to `y = keras.layers.maximum([x1, x2])`
y = keras.layers.Maximum()([x1, x2])
out = keras.layers.Dense(4)(y)
model = keras.models.Model(inputs=[input1, input2], outputs=out)

Attributes
input	Retrieves the input tensor(s) of a symbolic operation. Only returns the tensor(s) corresponding to the first time the operation was called.
output	Retrieves the output tensor(s) of a layer. Only returns the tensor(s) corresponding to the first time the operation was called.

Methods

from_config

View source

@classmethod
from_config(
    config
)

Creates an operation from its config.

This method is the reverse of get_config, capable of instantiating the same operation from the config dictionary.

Note: If you override this method, you might receive a serialized dtype config, which is a dict. You can deserialize it as follows:

if "dtype" in config and isinstance(config["dtype"], dict):
    policy = dtype_policies.deserialize(config["dtype"])

Args
config	A Python dictionary, typically the output of get_config.

Returns
An operation instance.