Returns the elementwise sum of a list of tensors.
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.
