tf.keras.ops.nanmin

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

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

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.

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

Examples:

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.]])