tf.math.add_n
Returns the element-wise sum of a list of tensors.
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, 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. |