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Averages a list of inputs element-wise..
Inherits From: Layer
, Operation
tf.keras.layers.Average(
**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.Average()([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.average([x1, x2])`
y = keras.layers.Average()([x1, x2])
out = keras.layers.Dense(4)(y)
model = keras.models.Model(inputs=[input1, input2], outputs=out)
Methods
from_config
@classmethod
from_config( config )
Creates a layer from its config.
This method is the reverse of get_config
,
capable of instantiating the same layer from the config
dictionary. It does not handle layer connectivity
(handled by Network), nor weights (handled by set_weights
).
Args | |
---|---|
config
|
A Python dictionary, typically the output of get_config. |
Returns | |
---|---|
A layer instance. |
symbolic_call
symbolic_call(
*args, **kwargs
)