Could not interpret optimizer identifier: <keras.src.optimizers.adam.Adam object
@hilmyas,
By default Tensorflow v2.16 uses keras v3.0 which might be the reason for the error you are facing. As the work-around, Could you please try to install keras 2 where the code was executed without any issue/error. Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/4cd97fa3a806aa1315ba193773225755/transfer_learning_with_movinet.ipynb).
```python
!pip install -U tf_keras # Keras 2
import os
os.environ["TF_USE_LEGACY_KERAS"] = "1"
```

Thank you!

 It works. Thanks for your help. @hilmyas,
Glad the issue is resolved for you, Could you please feel free to move this issue to closed status. Thank you! 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/64250">Yes</a>
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/64250">No</a>

### Issue type

Documentation Bug

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

Yes

### Source

source

### TensorFlow version

2.16.1

### Custom code

No

### 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?

Some days ago, I tried to run codes by using Google Colab from a tutorial of [transfer learning with movinet](https://github.com/tensorflow/docs/blob/master/site/en/tutorials/video/transfer_learning_with_movinet.ipynb) without any error. Today, I tried to run codes by using Google Colab from the same tutorial and it produced error when I tried to compile the model.

`num_epochs = 2

loss_obj = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)

optimizer = tf.keras.optimizers.Adam(learning_rate = 0.001)

model.compile(loss=loss_obj, optimizer=optimizer, metrics=['accuracy'])`

### Standalone code to reproduce the issue

```shell
https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/video/transfer_learning_with_movinet.ipynb#scrollTo=dVqBLrn1tBsd
```


### Relevant log output

```shell
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-12-0c295092a661> in <cell line: 7>()
      5 optimizer = tf.keras.optimizers.Adam(learning_rate = 0.001)
      6 
----> 7 model.compile(loss=loss_obj, optimizer=optimizer, metrics=['accuracy'])

/usr/local/lib/python3.10/dist-packages/tf_keras/src/utils/traceback_utils.py in error_handler(*args, **kwargs)
     68             # To get the full stack trace, call:
     69             # `tf.debugging.disable_traceback_filtering()`
---> 70             raise e.with_traceback(filtered_tb) from None
     71         finally:
     72             del filtered_tb

/usr/local/lib/python3.10/dist-packages/tf_keras/src/optimizers/__init__.py in get(identifier, **kwargs)
    333         )
    334     else:
--> 335         raise ValueError(
    336             f"Could not interpret optimizer identifier: {identifier}"
    337         )

ValueError: Could not interpret optimizer identifier: <keras.src.optimizers.adam.Adam object at 0x7af7a01536d0>
```
