# tf.math.top_k

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|---|---|
| [![](https://www.tensorflow.org/images/tf_logo_32px.png) TensorFlow 2 version](https://www.tensorflow.org/api_docs/python/tf/math/top_k) | [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/nn_ops.py#L4320-L4347) |

Finds values and indices of the `k` largest entries for the last dimension.

#### View aliases


**Main aliases**

[`tf.nn.top_k`](https://www.tensorflow.org/api_docs/python/tf/math/top_k)
**Compat aliases for migration**

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

[`tf.compat.v1.math.top_k`](https://www.tensorflow.org/api_docs/python/tf/math/top_k), [`tf.compat.v1.nn.top_k`](https://www.tensorflow.org/api_docs/python/tf/math/top_k), \`tf.compat.v2.math.top_k\`, \`tf.compat.v2.nn.top_k\`

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    tf.math.top_k(
        input, k=1, sorted=True, name=None
    )

If the input is a vector (rank=1), finds the `k` largest entries in the vector
and outputs their values and indices as vectors. Thus `values[j]` is the
`j`-th largest entry in `input`, and its index is `indices[j]`.

For matrices (resp. higher rank input), computes the top `k` entries in each
row (resp. vector along the last dimension). Thus,

    values.shape = indices.shape = input.shape[:-1] + [k]

If two elements are equal, the lower-index element appears first.

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| ## Args ||
|---|---|
| `input` | 1-D or higher `Tensor` with last dimension at least `k`. |
| `k` | 0-D `int32` `Tensor`. Number of top elements to look for along the last dimension (along each row for matrices). |
| `sorted` | If true the resulting `k` elements will be sorted by the values in descending order. |
| `name` | Optional name for the operation. |

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| ## Returns ||
|---|---|
| `values` | The `k` largest elements along each last dimensional slice. |
| `indices` | The indices of `values` within the last dimension of `input`. |

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