Unexpected NaN when invoking apis combination of tf.GradientTape().jacobian and tf.multiply and tf.math.reciprocal
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### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.13

### Custom code

Yes

### OS platform and distribution

_No response_

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

```python
import tensorflow as tf
import numpy as np

with tf.device("/cpu:0"):
  def test(a,b):
    with tf.GradientTape() as tape_1:
      tape_1.watch(a)
      tape_1.watch(b)
      w = a * tf.math.reciprocal(b)
      print(w)
    grad_1 = tape_1.jacobian(w, a)
    return grad_1


  a = tf.constant([3], dtype=tf.float32)
  b = tf.constant([0, 2, 3], dtype=tf.float32)

  cpu_output_1 = test(a,b)

with tf.device("/gpu:0"):
  def test(a, b):
    with tf.GradientTape() as tape_1:
      tape_1.watch(a)
      tape_1.watch(b)

      w = a * tf.math.reciprocal(b)
    grad_1 = tape_1.jacobian(w, a)
    return grad_1


  a = tf.constant([3], dtype=tf.float32)
  b = tf.constant([0, 2, 3], dtype=tf.float32)

  gpu_output_1 = test(a, b)

print(cpu_output_1)
print(gpu_output_1)


### Standalone code to reproduce the issue

```shell
Unexpected NaN when invoking apis combination of tf.GradientTape().jacobian and tf.multiply and tf.math.reciprocal
```


### Relevant log output

```shell
tf.Tensor([inf 1.5 1. ], shape=(3,), dtype=float32)
tf.Tensor(
[[inf]
 [nan]
 [nan]], shape=(3, 1), dtype=float32)
tf.Tensor(
[[inf]
 [nan]
 [nan]], shape=(3, 1), dtype=float32)
```
