tf.keras.layers.subtract
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Functional interface to the Subtract
layer.
tf.keras.layers.subtract(
inputs, **kwargs
)
Arguments |
inputs
|
A list of input tensors (exactly 2).
|
**kwargs
|
Standard layer keyword arguments.
|
Returns |
A tensor, the difference of the inputs.
|
Examples:
import keras
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)
subtracted = keras.layers.subtract([x1, x2])
out = keras.layers.Dense(4)(subtracted)
model = keras.models.Model(inputs=[input1, input2], outputs=out)
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Last updated 2021-02-18 UTC.
[null,null,["Last updated 2021-02-18 UTC."],[],[],null,["# tf.keras.layers.subtract\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/keras/layers/subtract) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.4.0/tensorflow/python/keras/layers/merge.py#L774-L800) |\n\nFunctional interface to the `Subtract` layer.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.keras.layers.subtract`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/subtract)\n\n\u003cbr /\u003e\n\n tf.keras.layers.subtract(\n inputs, **kwargs\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Arguments --------- ||\n|------------|--------------------------------------|\n| `inputs` | A list of input tensors (exactly 2). |\n| `**kwargs` | Standard layer keyword arguments. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A tensor, the difference of the inputs. ||\n\n\u003cbr /\u003e\n\n#### Examples:\n\n import keras\n\n input1 = keras.layers.Input(shape=(16,))\n x1 = keras.layers.Dense(8, activation='relu')(input1)\n input2 = keras.layers.Input(shape=(32,))\n x2 = keras.layers.Dense(8, activation='relu')(input2)\n subtracted = keras.layers.subtract([x1, x2])\n\n out = keras.layers.Dense(4)(subtracted)\n model = keras.models.Model(inputs=[input1, input2], outputs=out)"]]