tf.keras.ops.nanmean

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

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

x Input tensor.
axis Axis or axes along which the mean is computed. The default is to compute the mean 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. Defaults to False.

Output tensor containing the mean, 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.nanmean(x)
1.75
 
ops.nanmean(x, axis=1)
array([2., 1.5])
 
ops.nanmean(x, axis=1, keepdims=True)
array([[2. ],
       [1.5]])