tf.keras.layers.Maximum | TensorFlow v2.16.1 (original) (raw)
tf.keras.layers.Maximum
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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
@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
)