tf.keras.ops.percentile
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Compute the q-th percentile(s) of the data along the specified axis.
tf.keras.ops.percentile(
x, q, axis=None, method='linear', keepdims=False
)
Args |
x
|
Input tensor.
|
q
|
Percentile or sequence of percentiles to compute.
Values must be between 0 and 100 inclusive.
|
axis
|
Axis or axes along which the percentiles are computed.
|
method
|
A string specifies the method to use for estimating the
percentile. Available methods are "linear", "lower", "higher",
"midpoint", and "nearest". Defaults to "linear".
If the desired percentile lies between two data points i < j:
"linear": i + (j - i) * fraction, where fraction is the
fractional part of the index surrounded by i and j.
"lower": i.
"higher": j.
"midpoint": (i + j) / 2
"nearest": i or j, whichever is nearest.
|
keepdims
|
If True, reduced axes are kept with size 1.
|
Returns |
The percentile(s). If q is a single percentile and axis=None, then
the result is a scalar. If multiple percentile levels are given, the
first axis of the result corresponds to the percentiles. The other axes
are the axes that remain after the reduction of x.
|
Examples:
import keras
from keras import ops
x = keras.ops.array([1., 2., 3., 4.])
keras.ops.percentile(x, 50)
2.5
x = keras.ops.array([1., 2., 3., 4.])
keras.ops.percentile(x, [25, 75])
array([1.75, 3.25])
x = keras.ops.array([[1., 2., 3.],
[4., 5., 6.]])
keras.ops.percentile(x, 50, axis=1)
array([2., 5.])
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Last updated 2026-10-31 UTC.
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