tf.raw_ops.UniqueWithCounts
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Finds unique elements in a 1-D tensor.
View aliases
Compat aliases for migration
See
Migration guide for
more details.
tf.compat.v1.raw_ops.UniqueWithCounts
tf.raw_ops.UniqueWithCounts(
x,
out_idx=tf.dtypes.int32
,
name=None
)
This operation returns a tensor y
containing all of the unique elements of x
sorted in the same order that they occur in x
. This operation also returns a
tensor idx
the same size as x
that contains the index of each value of x
in the unique output y
. Finally, it returns a third tensor count
that
contains the count of each element of y
in x
. In other words:
y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1]
For example:
# tensor 'x' is [1, 1, 2, 4, 4, 4, 7, 8, 8]
y, idx, count = unique_with_counts(x)
y ==> [1, 2, 4, 7, 8]
idx ==> [0, 0, 1, 2, 2, 2, 3, 4, 4]
count ==> [2, 1, 3, 1, 2]
Args |
x
|
A Tensor . 1-D.
|
out_idx
|
An optional tf.DType from: tf.int32, tf.int64 . Defaults to tf.int32 .
|
name
|
A name for the operation (optional).
|
Returns |
A tuple of Tensor objects (y, idx, count).
|
y
|
A Tensor . Has the same type as x .
|
idx
|
A Tensor of type out_idx .
|
count
|
A Tensor of type out_idx .
|
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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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26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.UniqueWithCounts\n\n\u003cbr /\u003e\n\nFinds unique elements in a 1-D tensor.\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.UniqueWithCounts`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/UniqueWithCounts)\n\n\u003cbr /\u003e\n\n tf.raw_ops.UniqueWithCounts(\n x,\n out_idx=../../tf/dtypes#int32,\n name=None\n )\n\nThis operation returns a tensor `y` containing all of the unique elements of `x`\nsorted in the same order that they occur in `x`. This operation also returns a\ntensor `idx` the same size as `x` that contains the index of each value of `x`\nin the unique output `y`. Finally, it returns a third tensor `count` that\ncontains the count of each element of `y` in `x`. In other words:\n\n`y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1]`\n\n#### For example:\n\n # tensor 'x' is [1, 1, 2, 4, 4, 4, 7, 8, 8]\n y, idx, count = unique_with_counts(x)\n y ==\u003e [1, 2, 4, 7, 8]\n idx ==\u003e [0, 0, 1, 2, 2, 2, 3, 4, 4]\n count ==\u003e [2, 1, 3, 1, 2]\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------|-----------------------------------------------------------------------------------------------------------------------|\n| `x` | A `Tensor`. 1-D. |\n| `out_idx` | An optional [`tf.DType`](../../tf/dtypes/DType) from: `tf.int32, tf.int64`. Defaults to [`tf.int32`](../../tf#int32). |\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 (y, idx, count). ||\n| `y` | A `Tensor`. Has the same type as `x`. |\n| `idx` | A `Tensor` of type `out_idx`. |\n| `count` | A `Tensor` of type `out_idx`. |\n\n\u003cbr /\u003e"]]