tf.math.add_n
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Adds all input tensors element-wise.

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Main aliases

tf.add_n

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.add_n, tf.compat.v1.math.add_n

tf.math.add_n(
    inputs, name=None
)

tf.math.add_n performs the same operation as tf.math.accumulate_n.

This op does not broadcast its inputs. If you need broadcasting, use tf.math.add (or the + operator) instead.

For example:

a = tf.constant([[3, 5], [4, 8]])
b = tf.constant([[1, 6], [2, 9]])
tf.math.add_n([a, b, a])
<tf.Tensor: shape=(2, 2), dtype=int32, numpy=
array([[ 7, 16],
       [10, 25]], dtype=int32)>

Args
`inputs`	A list of `tf.Tensor` or `tf.IndexedSlices` objects, each with the same shape and type. `tf.IndexedSlices` objects will be converted into dense tensors prior to adding.
`name`	A name for the operation (optional).

Returns
A `tf.Tensor` of the same shape and type as the elements of `inputs`.

Raises
`ValueError`	If `inputs` don't all have same shape and dtype or the shape cannot be inferred.

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Last updated 2022-11-04 UTC.

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tf.math.add_n
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