Different Behavior of tf.raw_ops.Acos with jit_compile=True
Hi @**zoux1a ,**

I have replicated the reported behaviour with jit_compile=True and with jit_compile = False as well. It works with jit_compile=False. I attached a [gist](https://colab.research.google.com/gist/Venkat6871/64a54987d4df72b511db65d2b9bc71bd/62280_gpu-214-v.ipynb) for your reference.

Thank you! It seems this bug is about Acos? At least the reproducer is for Acos. Hi @zoux1a , @akuegel 

The results with `jit_compile` and without `jit_compile` seems differing more than 100% and even increase if the value of input increases if we calculate like `[(res_xla-res_eager)/res_xla]` . The difference seems large for me as it is not just precision difference.

Attaching [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/46fa1bc78ccc81c4d3ed109fb5565d12/62280_r1.ipynb#scrollTo=UfbnkQyT6ur-) for my exercise on this. Can the title and the bug description please be adjusted to *Acos* instead of *Asin*? All the reproducers I saw here are for Acos, so it seems this is what the bug is about?
### Issue type

Bug

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

No

### Source

source

### TensorFlow version

2.14.0

### Custom code

Yes

### OS platform and distribution

Ubuntu 22.04.3 LTS (x86_64)

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

11.8

### GPU model and memory

GPU 0: NVIDIA GeForce RTX 2070 GPU 1: NVIDIA GeForce RTX 2070 GPU 2: NVIDIA GeForce RTX 2070 GPU 3: NVIDIA GeForce RTX 2070

### Current behavior?

When the **tf.raw_ops.Acos** operation is invoked within a tf.function with JIT compilation enabled (**jit_compile=True**), it produces different results compared to the same operation called without JIT compilation. This inconsistency is observed when the code is executed on a **GPU** device.

### Standalone code to reproduce the issue

```shell
I can reproduce this issue on colab: https://colab.research.google.com/drive/1SJWDSLO8pIIVYfZYv1M8gFaUiOyX--MI?usp=sharing
```


### Relevant log output

```shell
File "/home/guihuan/LLM/results/tf-2/2023-10-22-20-21/test.py", line 50, in <module>
    tf.debugging.assert_near(no_op_res, op_res, atol=0.001, rtol=0.001)
  File "/home/guihuan/.conda/envs/night/lib/python3.9/site-packages/tensorflow/python/util/traceback_utils.py", line 153, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/home/guihuan/.conda/envs/night/lib/python3.9/site-packages/tensorflow/python/ops/control_flow_assert.py", line 102, in Assert
    raise errors.InvalidArgumentError(
tensorflow.python.framework.errors_impl.InvalidArgumentError: Expected 'tf.Tensor(False, shape=(), dtype=bool)' to be true. Summarized data: b''
b'x and y not equal to tolerance rtol = tf.Tensor(0.001, shape=(), dtype=float32), atol = tf.Tensor(0.001, shape=(), dtype=float32)'
b'x (shape=(10, 9) dtype=complex64) = '
(2.0430856-14.103499j), (2.0611959+14.493816j), (2.392881+13.213637j), ...
b'y (shape=(10, 9) dtype=complex64) = '
(2.0430856-14.103499j), 3.465736j, 4.158883j, ...
```
