TFLite model cannot slice a zero-dim tensor
I was able to reproduce this issue. Please find this [gist](https://colab.research.google.com/gist/pjpratik/d4ec293ef89703c4a3eb2c119ae4ec9b/61899.ipynb) and also a  similiar issue #57084.

@pkgoogle Could you please look into this issue?

Thanks. I was able to reproduce with the same gists, while we don't necessarily guarantee consistent behavior between Keras API and TFLite, this might be worth a look. @haozha111 can you please take a look? Do we expect TFLite to behave this way, should we standardize to Keras API behavior?
### 1. System information

- OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 20.04
- TensorFlow installation (pip package or built from source): pip
- TensorFlow library (version, if pip package or github SHA, if built from source): 2.15.0-dev20230918


### 2. Code

```
import tensorflow as tf

class Model(tf.keras.Model):
  def __init__(self):
    super(Model, self).__init__()

  def call(self, x):
    values, indices = tf.math.top_k(x, k=2, sorted=False)
    y = tf.slice(values, tf.constant([0, 0]), tf.constant([0, 1]))
    return y

# Initializing the model
m = Model()

# Inputs to the model
x = tf.constant([1., 2.], shape=[1, 2])

expected_value = m(x)
print(expected_value.numpy())


converter = tf.lite.TFLiteConverter.from_keras_model(m)
tflite_model = converter.convert()

def _evaluateTFLiteModel(tflite_model, input_data):
    interpreter = tf.lite.Interpreter(model_content=tflite_model)
    interpreter.allocate_tensors()
    input_details = interpreter.get_input_details()
    output_details = interpreter.get_output_details()

    for i in range(len(input_data)):
        interpreter.set_tensor(input_details[i]['index'], input_data[i])
    interpreter.invoke()
    output_data = [interpreter.get_tensor(output_details[i]['index'])
                   for i in range(len(output_details))]
    return output_data


actual_value = _evaluateTFLiteModel(tflite_model,[x])
print('tflite model output:')
print(actual_value[0])
```


### 3. Failure after conversion
Output:
```
keras model output:
[]
...

ValueError: Invalid tensor size.
```
The conversion is successful, but it throws an error during inference. This is because the `size` to `tf.slice` contains zero. If we change `size` to `[1,1]`, there's no error.

I think tflite model should support slice size = 0, similar to the original model.