Different Behavior of tf.raw_ops.Acos+tf.raw_ops.Xlogy with jit_compile=True 
I was able to reproduce the issue on tensorflow v2.14 and tf-nightly. Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/25172d93dd8d9981d8e84547a0046cfd/untitled1420.ipynb). Hi,

The difference in behavior can not be considered as an error, since it might be happening due to fusion operation in JIT compilation this ultimately result in less precise answer. Thank you! This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you. This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further. Are you satisfied with the resolution of your issue?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/62235">Yes</a>
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### 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+tf.raw_ops.Xlogy** 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 **CPU** device.



### Standalone code to reproduce the issue

```shell
import tensorflow as tf
import traceback

class Network(tf.Module):
    def __init__(self):
        super().__init__()

    @tf.function(jit_compile=True)
    def __call__(self, x):
      real_part = tf.random.normal([1, 10, 1, 1, 8], dtype=tf.float64)
      imag_part = tf.random.normal([1, 10, 1, 1, 8], dtype=tf.float64)
      tensor = tf.complex(real_part, imag_part)
      tensor = tf.cast(tensor, dtype=tf.complex128)
      x = tf.raw_ops.Acos(x=x, )        
      x = tf.raw_ops.Xlogy(y=x, x=tensor)
      return x

m = Network()
real_part = tf.random.normal([10, 9, 8], dtype=tf.float64)
imag_part = tf.random.normal([10, 9, 8], dtype=tf.float64)
tensor = tf.complex(real_part, imag_part)
tensor = tf.cast(tensor, dtype=tf.complex128)
inp = {
    "x": tensor,
}

with tf.device('/CPU:0'):
    tf.config.run_functions_eagerly(True)
    no_op_res = m(**inp)
    tf.config.run_functions_eagerly(False)
    with tf.device('/CPU:0'):
        op_res = m(**inp)

    tf.debugging.assert_near(tf.cast(no_op_res, tf.float64), tf.cast(op_res, tf.float64), atol=0.001, rtol=0.001)
```


### Relevant log output

```shell
File "/home/guihuan/LLM/results/tf-2/2023-10-22-20-21/test.py", line 34, in <module>
    tf.debugging.assert_near(tf.cast(no_op_res, tf.float64), tf.cast(op_res, tf.float64), 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=float64), atol = tf.Tensor(0.001, shape=(), dtype=float64)'
b'x (shape=(1, 10, 10, 9, 8) dtype=float64) = '
-0.05185302330670599, -0.15348608132964178, -0.1848064102102949, ...
b'y (shape=(1, 10, 10, 9, 8) dtype=float64) = '
-0.7967820214034921, -0.1360080982477385, 0.42889388296575726, ...
```
