`SystemError` in `tf.signal.frame` when `dtype` of `frame_step` is `tf.uint64` and its value is too large. 
Hi **@xl1043237213** ,
I tried to run your code on colab using TF-nightly and faced the same issue. Please find the [gist](https://colab.sandbox.google.com/gist/Venkat6871/4d103416aefde7f6ff9721b154d494a8/64923_2-17.ipynb) here for reference.

Thank you!
### Issue type

Bug

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

Yes

### Source

binary

### TensorFlow version

tf 2.15

### Custom code

No

### OS platform and distribution

Linux Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.10

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

When the `dtype` of `frame_step` in `tf.signal.frame` is `tf.uint64` and its value is close to 2^64,`SystemError` will be triggered.
Taking `frame_step = tf.constant(18446744069414584320, dtype=tf.uint64)` as an example, in eager mode, the API will trigger a `SystemError` when it is called.
But there is something very strange. This error can only be triggered once in the same runtime environment, after which Python can correctly recognize the dtype difference between the arguments in the execution, and the error message changes from `SystemError` to `InvalidArgumentError`. I don't know what happened.

### Standalone code to reproduce the issue

```shell
https://colab.research.google.com/drive/1fx6qyTVXmPW8YWUN_IBNCmrTLn90N0St?usp=sharing
```


### Relevant log output

```shell
SystemError: <class 'tensorflow.python.framework.ops.EagerTensor'> returned a result with an exception set
```
