tf.keras.layers.Activation

TensorFlow 1 version

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Layer that adds a list of inputs.

Inherits From: Layer, Module

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.layers.Add

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)

Arguments
`**kwargs`	standard layer keyword arguments.

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.keras / layers / layers.Activation

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Examples:

Arguments