tf.keras.ops.nanmin

Minimum of a tensor over the given axes, ignoring NaNs.

Main aliases

tf.keras.ops.numpy.nanmin

tf.keras.ops.nanmin(
    x, axis=None, keepdims=False
)

Args
`x`	Input tensor.
`axis`	Axis or axes along which the minimum is computed. The default is to compute the minimum of the flattened tensor.
`keepdims`	If this is set to `True`, the axes which are reduced are left in the result as dimensions with size one.

Returns
Output tensor containing the minimum, with NaN values ignored. If all values along a reduced axis are NaN, the result is NaN.

import numpy as np
from keras import ops
x = np.array([[1.0, np.nan, 3.0],
              [np.nan, 2.0, 1.0]])
ops.nanmin(x)
1.0

ops.nanmin(x, axis=1)
array([1., 1.])

ops.nanmin(x, axis=1, keepdims=True)
array([[1.],
       [1.]])

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.

Last updated 2026-10-31 UTC.

tf.keras.ops.nanmin Stay organized with collections Save and categorize content based on your preferences.