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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`

, but it waits for all of its inputs to be ready before beginning to sum. This buffering can result in higher memory consumption when inputs are ready at different times, since the minimum temporary storage required is proportional to the input size rather than the output size.

This op does not broadcast its inputs. If you need broadcasting, use `tf.math.add`

(or the `+`

operator) instead.

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. |

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/math/add_n