Functional interface to the Multiply layer.
tf.keras.layers.multiply(
inputs, **kwargs
)
Example:
x1 = np.arange(3.0)
x2 = np.arange(3.0)
tf.keras.layers.multiply([x1, x2])
<tf.Tensor: shape=(3,), dtype=float32, numpy=array([0., 1., 4.], ...)>
Usage in a functional model:
input1 = tf.keras.layers.Input(shape=(16,))
x1 = tf.keras.layers.Dense(
8, activation='relu')(input1) #shape=(None, 8)
input2 = tf.keras.layers.Input(shape=(32,))
x2 = tf.keras.layers.Dense(
8, activation='relu')(input2) #shape=(None, 8)
out = tf.keras.layers.multiply([x1,x2]) #shape=(None, 8)
out = tf.keras.layers.Dense(4)(out)
model = tf.keras.models.Model(inputs=[input1, input2], outputs=out)
Args |
|---|
inputs
|
A list of input tensors.
|
**kwargs
|
Standard layer keyword arguments.
|
Returns |
|---|
|
A tensor, the element-wise product of the inputs.
|
View source on GitHub