Broken ExtensionType interoperability with Keras in 2.16
Hi **@karelhorak-gen** ,
- Sorry for the delay, I tried to run your code on colab using TF v2.15, 2.16.1, nightly and in 2.15 it is working fine, remaining versions getting the same issue. please find the [gist](https://colab.sandbox.google.com/gist/Venkat6871/63cf5b4bc484ac837ff24245b4c3356d/67334_2-15-2-16-1-nightly.ipynb) here for reference.
- And Please post this issue on [keras-team/keras repo.](https://github.com/keras-team/keras/issues)
To know more see;
[https://discuss.tensorflow.org/t/keras-project-moved-to-new-repository-in-https-github-com-keras-team-keras/1999](https://discuss.tensorflow.org/t/keras-project-moved-to-new-repository-in-https-github-com-keras-team-keras/1999).
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. This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further. Are you satisfied with the resolution of your issue?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/67334">Yes</a>
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### Issue type

Bug

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

No

### Source

binary

### TensorFlow version

v2.16.1-0-g5bc9d26649c 2.16.1

### Custom code

No

### OS platform and distribution

MacOS 14.4.1 (Arm)

### 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?

The [ExtensionType guide](https://www.tensorflow.org/guide/extension_type#keras) suggests that it is possible to create `tf.keras.layers.Input` for ExtensionTypes using the `type_spec` argument. This argument, however, seems to be missing in Keras 3 / TF 2.16. It is not clear how the integration with Keras should work in 2.16 (if it is even possible due to the absence of the critical argument).

### Standalone code to reproduce the issue

```shell
# Taken from the guide for reference (https://www.tensorflow.org/guide/extension_type#keras):

class Network(tf.experimental.BatchableExtensionType):
  shape: tf.TensorShape  # batch shape. A single network has shape=[].
  work: tf.Tensor        # work[*shape, n] = work left to do at node n
  bandwidth: tf.Tensor   # bandwidth[*shape, n1, n2] = bandwidth from n1->n2

  def __init__(self, work, bandwidth):
    self.work = tf.convert_to_tensor(work)
    self.bandwidth = tf.convert_to_tensor(bandwidth)
    work_batch_shape = self.work.shape[:-1]
    bandwidth_batch_shape = self.bandwidth.shape[:-2]
    self.shape = work_batch_shape.merge_with(bandwidth_batch_shape)

  def __repr__(self):
    return network_repr(self)


input_spec = Network.Spec(shape=None,
                          work=tf.TensorSpec(None, tf.float32),
                          bandwidth=tf.TensorSpec(None, tf.float32))
model = tf.keras.Sequential([
    tf.keras.layers.Input(type_spec=input_spec),
    # BalanceNetworkLayer(),
    ])
```


### Relevant log output

```shell
TypeError: Input() got an unexpected keyword argument 'type_spec'
```
