tf.keras.layers.Concatenate

Layer that concatenates a list of inputs.

Inherits From: Layer, Module

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Compat aliases for migration

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tf.compat.v1.keras.layers.Concatenate

tf.keras.layers.Concatenate(
    axis=-1, **kwargs
)

It takes as input a list of tensors, all of the same shape except for the concatenation axis, and returns a single tensor that is the concatenation of all inputs.

x = np.arange(20).reshape(2, 2, 5)
print(x)
[[[ 0  1  2  3  4]
  [ 5  6  7  8  9]]
 [[10 11 12 13 14]
  [15 16 17 18 19]]]
y = np.arange(20, 30).reshape(2, 1, 5)
print(y)
[[[20 21 22 23 24]]
 [[25 26 27 28 29]]]
tf.keras.layers.Concatenate(axis=1)([x, y])
<tf.Tensor: shape=(2, 3, 5), dtype=int64, numpy=
array([[[ 0,  1,  2,  3,  4],
        [ 5,  6,  7,  8,  9],
        [20, 21, 22, 23, 24]],
       [[10, 11, 12, 13, 14],
        [15, 16, 17, 18, 19],
        [25, 26, 27, 28, 29]]])>

x1 = tf.keras.layers.Dense(8)(np.arange(10).reshape(5, 2))
x2 = tf.keras.layers.Dense(8)(np.arange(10, 20).reshape(5, 2))
concatted = tf.keras.layers.Concatenate()([x1, x2])
concatted.shape
TensorShape([5, 16])

Args
axis	Axis along which to concatenate.
**kwargs	standard layer keyword arguments.