tf.math.add_n

Returns the element-wise sum of a list of tensors.

View aliases

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
)

All inputs in the list must have the same shape. 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]).numpy()
array([[ 7, 16],
       [10, 25]], dtype=int32)

See Also:

• tf.reduce_sum(inputs, axis=0) - This performs the same mathematical operation, but tf.add_n may be more efficient because it sums the tensors directly. reduce_sum on the other hand calls tf.convert_to_tensor on the list of tensors, unnecessarily stacking them into a single tensor before summing.

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.