Adds all input tensors element-wise.
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.
|
View source on GitHub