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# tf.math.top_k

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

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.

`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.

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

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]