tf.raw_ops.TopK
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Finds values and indices of the k largest elements for the last dimension.
tf.raw_ops.TopK(
input, k, 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.
If k varies dynamically, use TopKV2 below.
Args |
|---|
input
|
A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64.
1-D or higher with last dimension at least k.
|
k
|
An int that is >= 0.
Number of top elements to look for along the last dimension (along each
row for matrices).
|
sorted
|
An optional bool. Defaults to True.
If true the resulting k elements will be sorted by the values in
descending order.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A tuple of Tensor objects (values, indices).
|
values
|
A Tensor. Has the same type as input.
|
indices
|
A Tensor of type int32.
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.raw_ops.TopK\n\n\u003cbr /\u003e\n\nFinds values and indices of the `k` largest elements for the last dimension.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.TopK`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/TopK)\n\n\u003cbr /\u003e\n\n tf.raw_ops.TopK(\n input, k, sorted=True, name=None\n )\n\nIf the input is a vector (rank-1), finds the `k` largest entries in the vector\nand outputs their values and indices as vectors. Thus `values[j]` is the\n`j`-th largest entry in `input`, and its index is `indices[j]`.\n\nFor matrices (resp. higher rank input), computes the top `k` entries in each\nrow (resp. vector along the last dimension). Thus, \n\n values.shape = indices.shape = input.shape[:-1] + [k]\n\nIf two elements are equal, the lower-index element appears first.\n\nIf `k` varies dynamically, use `TopKV2` below.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `input` | A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `int64`, `bfloat16`, `uint16`, `half`, `uint32`, `uint64`. 1-D or higher with last dimension at least `k`. |\n| `k` | An `int` that is `\u003e= 0`. Number of top elements to look for along the last dimension (along each row for matrices). |\n| `sorted` | An optional `bool`. Defaults to `True`. If true the resulting `k` elements will be sorted by the values in descending order. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|-----------|-------------------------------------------|\n| A tuple of `Tensor` objects (values, indices). ||\n| `values` | A `Tensor`. Has the same type as `input`. |\n| `indices` | A `Tensor` of type `int32`. |\n\n\u003cbr /\u003e"]]
