Returns the element-wise sum of a list of tensors.
View aliases
Main aliases
Compat aliases for migrationSee Migration guide for more details.
tf.math.add_n(
inputs, name=None
)
Used in the notebooks
Used in the guide | Used in the tutorials |
---|---|
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, buttf.add_n
may be more efficient because it sums the tensors directly.reduce_sum
on the other hand callstf.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 .
|