# tf.sparse.maximum

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|---|---|
| [![](https://www.tensorflow.org/images/tf_logo_32px.png) TensorFlow 1 version](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/sparse/maximum) | [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/ops/sparse_ops.py#L2448-L2483) |

Returns the element-wise max of two SparseTensors.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.sparse.maximum`](https://www.tensorflow.org/api_docs/python/tf/sparse/maximum), [`tf.compat.v1.sparse_maximum`](https://www.tensorflow.org/api_docs/python/tf/sparse/maximum)

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    tf.sparse.maximum(
        sp_a, sp_b, name=None
    )

Assumes the two SparseTensors have the same shape, i.e., no broadcasting.
Example:

    sp_zero = sparse_tensor.SparseTensor([[0]], [0], [7])
    sp_one = sparse_tensor.SparseTensor([[1]], [1], [7])
    res = tf.sparse.maximum(sp_zero, sp_one).eval()
    # "res" should be equal to SparseTensor([[0], [1]], [0, 1], [7]).

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| ## Args ||
|---|---|
| `sp_a` | a `SparseTensor` operand whose dtype is real, and indices lexicographically ordered. |
| `sp_b` | the other `SparseTensor` operand with the same requirements (and the same shape). |
| `name` | optional name of the operation. |

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| ## Returns ||
|---|---|
| `output` | the output SparseTensor. |

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