tf.keras.layers.AlphaDropout crash when noise_shape is a tensor
@cheyennee I was able to replicate the issue reported [here](https://colab.research.google.com/gist/sushreebarsa/3006e9f5c94eb8adbad8f36ccb9010db/62421.ipynb). Could you please use a fixed value for noise_shape instead of a tensor as a workaround?
Thank you! Hi, @sushreebarsa. Using a fixed value for `noise_shape` works well. But I think it would be better if the documentation include details about the usage of `noise_shape` or that the error message generated `by tf.keras.layers.AlphaDropout` be improved to offer clearer guidance in the event of a crash.
### Issue type

Bug

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

No

### Source

source

### TensorFlow version

tf 2.14.0

### Custom code

Yes

### OS platform and distribution

windows colab

### 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?

In the documentation, there is no information provided for the `noise_shape` parameter. When the value of `noise_shape` is set as a tensor, the API crashes. It is recommended that the documentation include details about the usage of `noise_shape` or that the error message generated by `tf.keras.layers.AlphaDropout` be improved to offer clearer guidance in the event of a crash.

### Standalone code to reproduce the issue

```shell
import tensorflow as tf
__input___0_tensor = tf.random.uniform([3, 2, 3], minval=-1.0, maxval=0.04343286078799158, dtype=tf.float32)
__input___0 = tf.identity(__input___0_tensor)
noise_shape_tensor = tf.random.uniform([3, 2, 3, 1], minval=-2, maxval=2, dtype=tf.float32)
noise_shape = tf.identity(noise_shape_tensor)
rate = 0.5
seed = None
alpha_dropout_layer = tf.keras.layers.AlphaDropout(rate, noise_shape=noise_shape, seed=seed)
output = alpha_dropout_layer(__input___0)
print(output)
```


### Relevant log output

```shell
ValueError                                Traceback (most recent call last)
<ipython-input-30-fe6bb6d4ede4> in <cell line: 9>()
      7 seed = None
      8 alpha_dropout_layer = tf.keras.layers.AlphaDropout(rate, noise_shape=noise_shape, seed=seed)
----> 9 output = alpha_dropout_layer(__input___0)
     10 print(output)

1 frames
/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/ops.py in __bool__(self)
    300 
    301   def __bool__(self) -> bool:
--> 302     return bool(self._numpy())
    303 
    304   __nonzero__ = __bool__

ValueError: Exception encountered when calling layer 'alpha_dropout_12' (type AlphaDropout).

The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Call arguments received by layer 'alpha_dropout_12' (type AlphaDropout):
  • inputs=tf.Tensor(shape=(3, 2, 3), dtype=float32)
  • training=None
```
