tf.keras.layers.Add
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Layer that adds a list of inputs.
Inherits From: Layer, Module
tf.keras.layers.Add(
**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 = tf.random.normal(input_shape)
x2 = tf.random.normal(input_shape)
y = tf.keras.layers.Add()([x1, x2])
print(y.shape)
(2, 3, 4)
Used in a functional model:
input1 = tf.keras.layers.Input(shape=(16,))
x1 = tf.keras.layers.Dense(8, activation='relu')(input1)
input2 = tf.keras.layers.Input(shape=(32,))
x2 = tf.keras.layers.Dense(8, activation='relu')(input2)
# equivalent to `added = tf.keras.layers.add([x1, x2])`
added = tf.keras.layers.Add()([x1, x2])
out = tf.keras.layers.Dense(4)(added)
model = tf.keras.models.Model(inputs=[input1, input2], outputs=out)
Args |
|---|
**kwargs
|
standard layer keyword arguments.
|
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Last updated 2021-05-14 UTC.
[null,null,["Last updated 2021-05-14 UTC."],[],[],null,["# tf.keras.layers.Add\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/keras/layers/Add) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.5.0/tensorflow/python/keras/layers/merge.py#L218-L251) |\n\nLayer that adds a list of inputs.\n\nInherits From: [`Layer`](../../../tf/keras/layers/Layer), [`Module`](../../../tf/Module)\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.Add`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Add)\n\n\u003cbr /\u003e\n\n tf.keras.layers.Add(\n **kwargs\n )\n\nIt takes as input a list of tensors,\nall of the same shape, and returns\na single tensor (also of the same shape).\n\n#### Examples:\n\n input_shape = (2, 3, 4)\n x1 = tf.random.normal(input_shape)\n x2 = tf.random.normal(input_shape)\n y = tf.keras.layers.Add()([x1, x2])\n print(y.shape)\n (2, 3, 4)\n\nUsed in a functional model: \n\n input1 = tf.keras.layers.Input(shape=(16,))\n x1 = tf.keras.layers.Dense(8, activation='relu')(input1)\n input2 = tf.keras.layers.Input(shape=(32,))\n x2 = tf.keras.layers.Dense(8, activation='relu')(input2)\n # equivalent to `added = tf.keras.layers.add([x1, x2])`\n added = tf.keras.layers.Add()([x1, x2])\n out = tf.keras.layers.Dense(4)(added)\n model = tf.keras.models.Model(inputs=[input1, input2], outputs=out)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|------------|-----------------------------------|\n| `**kwargs` | standard layer keyword arguments. |\n\n\u003cbr /\u003e"]]
TensorFlow 1 version
View source on GitHub