QuantizeAndDequantizeV4 throws TypeError in gradient computation in forward mode
@trickiwoo Though i was able to replicate the issue [here](https://colab.research.google.com/gist/sushreebarsa/5af7133e302705296c699040acddd4de/60059.ipynb), please confirm if this is a duplicate ticket of [this](https://github.com/tensorflow/tensorflow/issues/59960) issue. If so please close this thread as we will follow up with the other one. Thank you! Hi @sushreebarsa , thanks for replicating it! It was a similar issue but for different APIs @trickiwoo Thank you for the confirmation.
@SuryanarayanaY Could you please have a look at this issue?
Thank you!
<details><summary>Click to expand!</summary> 
 
 ### Issue Type

Bug

### Have you reproduced the bug with TF nightly?

Yes

### Source

source

### Tensorflow Version

2.11

### 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 Behaviour?

```shell
QuantizeAndDequantizeV4 throws TypeError in gradient computation in forward mode. I encountered a similar issue (https://github.com/tensorflow/tensorflow/issues/59960) where quantize_and_dequantize_v2 is wrongly associated with _QuantizeAndDequantizeV4GradGrad in gradient computation. In this case, the V4 version API doesn't work either. It would be great if they could be fixed in the backend.
```


### Standalone code to reproduce the issue

```shell
import tensorflow as tf
import numpy as np

tensor = tf.random.uniform(shape=[1, 1], dtype=tf.float32)

def quantizeAndDequantize(x):

    y = tf.raw_ops.QuantizeAndDequantizeV4(input=x, input_min=0., input_max=5.)
    return y

output = quantizeAndDequantize(tensor) # pass
with tf.autodiff.ForwardAccumulator(tensor, tf.constant([[0.], [1.]])) as acc:
    output = quantizeAndDequantize(tensor)
```


### Relevant log output

```shell
TypeError: _QuantizeAndDequantizeV4GradGrad() takes 2 positional arguments but 4 were given
```
</details>