The result of tf.quantization.fake_quant_with_min_max_args is inconsistent between CPU and GPU
@sachinprasadhs I was able to replicate the issue reported here in [CPU](https://colab.research.google.com/gist/sushreebarsa/2216e9f37019c5fd21a3e8d88491197f/63271.ipynb) and [GPU](https://colab.research.google.com/gist/sushreebarsa/10de3e64c0048c2b85924488d7a2a969/untitled934.ipynb#scrollTo=ryI-x0hpVuC8). Please find the attached gists. Thank you!
### Issue type

Bug

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

Yes

### Source

binary

### TensorFlow version

tf 2.15

### Custom code

Yes

### OS platform and distribution

Linux Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.8

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

CUDA 12.2

### GPU model and memory

_No response_

### Current behavior?

For the same input, `tf.quantization.fake_quant_with_min_max_args ` produces inconsistent results on CPU and GPU.

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

input_data = tf.constant([0.0, 1.0, 2.0, 3.0, 4.0])

with tf.device('cpu:0'):
    quantized_input_data = tf.quantization.fake_quant_with_min_max_args(input_data, min=-6.0, max=6.0)
    print(quantized_input_data)

with tf.device('gpu:0'):
    quantized_input_data = tf.quantization.fake_quant_with_min_max_args(input_data, min=-6.0, max=6.0)
    print(quantized_input_data)
```


### Relevant log output

```shell
tf.Tensor([0.        0.9882353 2.0235295 3.0117648 4.       ], shape=(5,), dtype=float32)
tf.Tensor([0.        0.9882353 1.9764706 3.0117648 4.       ], shape=(5,), dtype=float32)
```
