How can I exit the XLAControlFlowContext when inside a jit_compile tf.function? Exit() function take no effect.
Hi **@MoFHeka** ,
Sorry for the delay, I tried to run your code on colab using tf 2.15, 2.16 and tf-nightly versions faced same issue. Please find the [gist](https://colab.sandbox.google.com/gist/Venkat6871/0d2b7992674f8e23a6f3cfd3e1bbe2f4/63632_2-15-2-16-nightly.ipynb) here for reference. We need to work on it, In few days i will provide a solution for it.

Thank you! Hi **@MoFHeka** ,
- The ctx.Exit() and ctx.Enter() methods are internal and their direct manipulation is generally not advisable due to potential instability and undefined behavior.
- I tried alternative approaches manually. I hope it will use for you. Here i am providing [gist](https://colab.sandbox.google.com/gist/Venkat6871/7d942ef79386b982a402b42218881fb5/63632_nightly-v.ipynb) for your reference.

Thank you! @Venkat6871 I'm afraid this proposal is not suitable for me as I am the developer of tensorflow recommender addon. I wanted to be able to be compatible with keras full graph XLA training without rewriting the new XlaOpKernel code.
### Issue type

Bug

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

No

### Source

binary

### TensorFlow version

tf 2.15

### Custom code

Yes

### OS platform and distribution

Ubuntu 22.04

### Python version

3.10

### CUDA/cuDNN version

CUDA12.3/cuDNN9.0

### GPU model and memory

GTX4090 24GiB

### Current behavior?

I have a custom op that is a normal OpKernel unable to be compile by XLA cluster. But unfortunately, when the user use this custom op, they have to wrap it into a tf.funtion. So somehow when the use Keras jit_compile or something else, errors happened.

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

@tf.function(jit_compile=True)
def test(a):
    b = a + a
    ctx = tf.__internal__.get_enclosing_xla_context()
    ctx.Exit()
    tf.print(b)
    ctx.Enter()
    return b * b

test(tf.constant(1))
```


### Relevant log output

```shell
2024-03-14 02:28:52.720666: W tensorflow/core/framework/op_kernel.cc:1745] OP_REQUIRES failed at xla_ops.cc:296 : INVALID_ARGUMENT: Detected unsupported operations when trying to compile graph __inference_test_9[_XlaMustCompile=true,config_proto=9241198235816212909,executor_type=11160318154034397263] on XLA_GPU_JIT: StringFormat (No registered 'StringFormat' OpKernel for XLA_GPU_JIT devices compatible with node {{node StringFormat}}){{node StringFormat}}
The op is created at: 
File "xla_context_test.py", line 12, in <module>
  test(tf.constant(1))
File "xla_context_test.py", line 8, in test
  tf.print(b)
Traceback (most recent call last):
  File "xla_context_test.py", line 12, in <module>
    test(tf.constant(1))
  File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/util/traceback_utils.py", line 153, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/execute.py", line 54, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InvalidArgumentError: Detected unsupported operations when trying to compile graph __inference_test_9[_XlaMustCompile=true,config_proto=9241198235816212909,executor_type=11160318154034397263] on XLA_GPU_JIT: StringFormat (No registered 'StringFormat' OpKernel for XLA_GPU_JIT devices compatible with node {{node StringFormat}}){{node StringFormat}}
The op is created at: 
File "xla_context_test.py", line 12, in <module>
  test(tf.constant(1))
File "xla_context_test.py", line 8, in test
  tf.print(b) [Op:__inference_test_9]
```
