Fails to convert to TFLite model in TF 2.16.0rc0
When a keras model is created with TF2.16.0 ([keras model available here)](https://www.dropbox.com/scl/fi/z0womeh2hj51i6tqj7wc0/TF2.16.0_model_classifier_CNN.keras?rlkey=c3dqmdqh3c516twhpdxjercg7&dl=0), the conversion still fails but with a different error:

[log2.txt](https://github.com/tensorflow/tensorflow/files/14324786/log2.txt)
 Hi @feranick, do you mind uploading the model on github via a zip file? There are licensing issues with dropbox so we cannot use it. Thanks for your help. The models are quite large and beyind the github 25MB limit. Here they are from an open server:

https://gridedgedm.mit.edu/tf_tmp/TF2.15.0_model_classifier_CNN.keras
https://gridedgedm.mit.edu/tf_tmp/TF2.16.0_model_classifier_CNN.keras
 Hi @feranick, I was able to replicate on 2.16 in this [gist](https://colab.sandbox.google.com/gist/pkgoogle/ed2e7fdf2acb7b0d9c8bbe5921cb64a3/62989.ipynb) (You have to upload your TF2.16.0... file to colab). Is there any particular ops you are using in this model or do you have any additional information on the creation of this model?

Hi @majiddadashi, can you please take a look? Thanks. > Hi @feranick, I was able to replicate on 2.16 in this [gist](https://colab.sandbox.google.com/gist/pkgoogle/ed2e7fdf2acb7b0d9c8bbe5921cb64a3/62989.ipynb) (You have to upload your TF2.16.0... file to colab). Is there any particular ops you are using in this model or do you have any additional information on the creation of this model?
> 
Hi @pkgoogle, thank you for looking into this. This below is a snapshot of the code relevant to the creation of the model. I hope it's helpful. I have been using it for a long time with TF2.15.0 and below with no issues...
[model.txt](https://github.com/tensorflow/tensorflow/files/14378663/model.txt)



 Here's also the `tf.lite.experimental.Analyzer.analyze(model_content=tflite_model)` output for both the TF2.15.0 and TF2.16.0rc0 models (the latter failing).
[analyzer_2.15_model.txt](https://github.com/tensorflow/tensorflow/files/14378749/analyzer_2.15_model.txt)
[analyzer_2.16_model.txt](https://github.com/tensorflow/tensorflow/files/14378750/analyzer_2.16_model.txt)

 If you casually compare the config.jason in the keras model files you can see that the variable `batch_input_shape` in TF2.15.0 was changed to `batch_shape` in TF2.16. This variable remain undefined in TF2.15. The config.json are attached.
[TF2.16rc0_config.json](https://github.com/tensorflow/tensorflow/files/14378950/TF2.16rc0_config.json)
[TF2.15_config.json](https://github.com/tensorflow/tensorflow/files/14378952/TF2.15_config.json)
 Even replacing `batch_shape` with `batch_input_shape`, there are still errors when converting the keras model into a tflite:
```
[/usr/local/lib/python3.10/dist-packages/keras/src/optimizers/optimizer.py](https://localhost:8080/#) in _process_kwargs(self, kwargs)
    140                 )
    141             else:
--> 142                 raise TypeError(
    143                     f"{k} is not a valid argument, kwargs should be empty "
    144                     " for `optimizer_experimental.Optimizer`."

TypeError: loss_scale_factor is not a valid argument, kwargs should be empty  for `optimizer_experimental.Optimizer`.
```
`loss_scale_factor` seems to be defined only in TF2.16.0, but there not in the TF2.15 model.
 Tested the above models with the pre-release, TF 2.16.0-rc0, using keras 3. Now they both crash. Log attached.
[TF2.15_convertLog.txt](https://github.com/tensorflow/tensorflow/files/14425168/TF2.15_convertLog.txt)
[TF2.16_convertLog.txt](https://github.com/tensorflow/tensorflow/files/14425169/TF2.16_convertLog.txt)

When used in "legacy" mode (using tf-keras~=2.16rc0), the crash is identical as my previous report above (i.e. old TF2.15 models are converted, new TF2.16 are not). So in summary: any model built with `TF2.15` or earlier or with `TF2.16.0-rc0` using `keras 2` (and `tf_keras=2.16rc0`) can be successfully converted in tflite. Any model built with `TF2.16.0-rc0` using `keras 3` **cannot** be converted to tflite. Any model built with `TF2.15` or earlier or with `TF2.16.0-rc0` using `keras 2` **cannot** be converted using `TF2.16.0-rc0` in keras 3 mode.

**In essence, conversion to tflite is completely broken with keras 3.** The models created with `keras v2` and `v3` appear to be completely incompatible with each other. The way to have a successful conversion is to basically do the training, model loading and conversion within the same keras version.
So for `keras v2`, saving after training:
```
import tf_keras as keras
model.save(dP.model_name)
```
for the TFlite conversion:
```
def convertModelToTFLite(model_file):
    import tensorflow as tf
    import tf_keras as keras
    model = keras.models.load_model(model_file)
    converter = tf.lite.TFLiteConverter.from_keras_model(model)    # TensorFlow 2.15 and earlier
    converter.optimizations = [tf.lite.Optimize.DEFAULT]
    tflite_model = converter.convert()
    tf.lite.experimental.Analyzer.analyze(model_content=tflite_model)
    open(convFile, "wb").write(tflite_model)
```
For loading a `v2` model:
```
model = keras.models.load_model(model_name)
```
For `keras v3`, saving after training:
```
import keras
model.export(dP.model_name)
```
For loading a `v3` model:
```
model = keras.models.Sequential()
model.add(keras.layers.TFSMLayer(model_name, call_endpoint='serve'))
```
for the TFlite conversion:
```
 def convertModelToTFLite(model_file):
    import tensorflow as tf
    import keras
    model = keras.layers.TFSMLayer(model_file, call_endpoint='serve') # TensorFlow >= 2.16.0
    converter = tf.lite.TFLiteConverter.from_keras_model(model)
   
    converter.optimizations = [tf.lite.Optimize.DEFAULT]
    tflite_model = converter.convert()
    tf.lite.experimental.Analyzer.analyze(model_content=tflite_model)
    open(convFile, "wb").write(tflite_model)
```

This of course is not ideal in the long term, when "legacy" `v2` models will require maintenance of legacy code to deal with it. **A solution could be an ad-hoc conversion API for models from `v2` to `v3`.**
### 1. System information

- Ubuntu 22.04
- Built from source, TF 2.16.0rc0
- TensorFlow library: TF 2.16.0 (branch r2.16), commit 03d0e0b
  
### 2. Code

Code attached.
[ConvertToTFLite.py.txt](https://github.com/tensorflow/tensorflow/files/14324713/ConvertToTFLite.py.txt)

### 3. Failure after conversion
Conversion of a model is successful when using TF2.15.0 or earlier. Conversion of a model created with TF2.15.0 or earlier fails when using TF 2.16.0 for conversion. [The initial keras model is available here.](https://www.dropbox.com/scl/fi/1ldtdr90qsgbns0snu2ba/TF2.15.0_model_classifier_CNN.keras?rlkey=lf1cm56oyt21v1xqer40t0b1w&dl=0) Log provided below.

### Log - attached.
[log.txt](https://github.com/tensorflow/tensorflow/files/14324717/log.txt)

