## Issue

I am trying to convert all `nan`

values to zero in my final results. I am not able to execute it properly!

The following is the code: also availvable on colab : link

```
import tensorflow as tf
import numpy as np
ts = tf.constant([[0,0]])
tx = tf.constant([[0,1]])
out = ts / (ts + fx)
out.numpy() # array([nan, 0.])
tf.math.is_nan(out).numpy() # array([ True, False]
out.numpy()[(tf.math.is_nan(out).numpy())] = 0
out.numpy() #array([nan, 0.])
```

`out.numpy()`

should give `array([0., 0.])`

## Solution

Change:

```
out.numpy()[(tf.math.is_nan(out).numpy())] = 0
```

To:

```
out = tf.where(tf.math.is_nan(out), 0., out)
```

Answered By – Djinn

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