tf.raw_ops.StringSplitV2 does not limit a number of splits by max_split attribute
@rkazants I was able to replicate the issue reported [here](https://colab.research.google.com/gist/sushreebarsa/620bf43013e6accbbad6b39ca6446670/66583.ipynb#scrollTo=QScJQq8WYQsk). Could you consider using tf.strings.split instead. It offers an optional max_split parameter to limit the number of splits: https://www.tensorflow.org/api_docs/python/tf/strings/split
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. Hi @sushreebarsa,

please remove stale label because the issue is not fixed.

Best regards,
Roman
### Issue type

Bug

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

Yes

### Source

source

### TensorFlow version

2.16.1

### 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 behavior?

tf.raw_ops.StringSplitV2 does not limit a number of splits by max_split attribute.

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

tf.raw_ops.StringSplitV2(input=['one<>'], sep='<>', maxsplit=1) # outputs two splits 'one' and '' instead of just one split

tf.raw_ops.StringSplitV2(input=['one<>two'], sep='<>', maxsplit=1) # outputs two splits 'one' and 'two' instead of just one split
```


### Relevant log output

```shell
>>> tf.raw_ops.StringSplitV2(input=['one<>'], sep='<>', maxsplit=1)
StringSplitV2(indices=<tf.Tensor: shape=(2, 2), dtype=int64, numpy=
array([[0, 0],
       [0, 1]])>, values=<tf.Tensor: shape=(2,), dtype=string, numpy=array([b'one', b''], dtype=object)>, shape=<tf.Tensor: shape=(2,), dtype=int64, numpy=array([1, 2])>)

>>> tf.raw_ops.StringSplitV2(input=['one<>two'], sep='<>', maxsplit=1)
StringSplitV2(indices=<tf.Tensor: shape=(2, 2), dtype=int64, numpy=
array([[0, 0],
       [0, 1]])>, values=<tf.Tensor: shape=(2,), dtype=string, numpy=array([b'one', b'two'], dtype=object)>, shape=<tf.Tensor: shape=(2,), dtype=int64, numpy=array([1, 2])>)
```
