keras outputs differently in different versions on tensorflow backend
@cheyennee Keras and TensorFlow undergo continuous development, and internal changes in their implementation can lead to subtle differences in the way models are executed and how outputs are generated. So it might give a different outcome which we expect to be better in every new release. We would recommend you to use the latest version as the older ones are not actively supported.
Thank you! Same problem can be found in this [model](https://drive.google.com/file/d/1gJXl0CHUwDMPN3oWsn0ztgCRC-YKALsv/view?usp=sharing). In version 2.14, model works well. while in version 2.3.1, it throws error: 
```
tensorflow.python.framework.errors_impl.InvalidArgumentError:  Only ranks up to 5 supported: [10,2,4,5,3,3]
	 [[node 15_dense/BiasAdd (defined at \software\anaconda\anaconda\envs\muffin3.6-1\lib\site-packages\tensorflow_core\python\framework\ops.py:1751) ]] [Op:__inference_keras_scratch_graph_10145]

Function call stack:
keras_scratch_graph
``` @cheyennee Thank you for your response here!
This issue  is not replicating the latest and we also recommend to use the newer version. Version 2.3.1 is not actively supported so could you please move this issue to closed status?
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/62592">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/62592">No</a>

### Issue type

Bug

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

Yes

### Source

source

### TensorFlow version

tf 2.14.0

### Custom code

Yes

### OS platform and distribution

windows colab

### Mobile device

_No response_

### Python version

3.10

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

I have a keras [model](https://drive.google.com/file/d/1RoNy5rs4vlOV37NmrTuRrf1GR_4FvY9V/view?usp=drive_link) and an [input](https://drive.google.com/file/d/126zU8p3Jm6HTqRoI4p1Lni1VMkM1QeGi/view?usp=drive_link). I use model to predict this input. I found that in keras v2.3.1, it predicts nan. However, in keras v2.14.0, it outputs normally.

### Standalone code to reproduce the issue

```shell
import keras
import numpy as np
print(keras.__version__)
from keras.datasets import mnist
(x_train,y_train),(x_test,y_test) = mnist.load_data()
model = keras.models.load_model('/content/322-tensorflow.h5')
input = np.load('/content/input.npy')
model.compile(loss='mean_squared_logarithmic_error', optimizer='adadelta')
history = model.fit(x_train, y_train)
model.predict(input)
```


### Relevant log output

```shell
keras v2.14.0

WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
1875/1875 [==============================] - 27s 11ms/step - loss: 6202843795574403104768.0000
1/1 [==============================] - 0s 408ms/step
array([[-1902.7032 ,   141.09955,  -277.39343,  1343.9507 ,  1219.6061 ,
          893.0104 ,   997.8686 ,  2026.3091 ,  -905.83954,  -349.66815]],
      dtype=float32)
```
keras v2.3.1
```
Epoch 1/1

10/10 [==============================] - 1s 104ms/step - loss: 97095230641965394441535488.0000
[[nan nan nan nan nan nan nan nan nan nan]]
```
```
