DistributedDatasetInterface is not an attribute of input_lib - engine\data_adapter.py
this is the same error I had: AttributeError: module 'tensorflow.python.distribute.input_lib' has no attribute 'DistributedDatasetInterface'. This error comes up even when I try model.fit and any other operation with the model beyond its compile line.  > this is the same error I had: AttributeError: module 'tensorflow.python.distribute.input_lib' has no attribute 'DistributedDatasetInterface'. This error comes up even when I try model.fit and any other operation with the model beyond its compile line.

I've solved it by replacing DistributedDatasetInterface by DistributedDatasetSpec right on: 
```
...\site-packages\tensorflow\python\keras\engine\data_adapter.py", line 1699, in _is_distributed_dataset
```

This is what I did:
```
def _is_distributed_dataset(ds):
#   return isinstance(ds, input_lib.DistributedDatasetInterface)
    return isinstance(ds, input_lib.DistributedDatasetSpec)
```

Definetely not a good practice, I know, but...  > return isinstance(ds, input_lib.DistributedDatasetSpec)

do you have any update if input_lib.DistributedDatasetSpec carries same functionality as input_lib.DistributedDatasetInterface ? @samuelsennev,
**tensorflow/python/keras** code is a legacy copy of Keras since the TensorFlow v2.7 release, and will be deleted in the v2.12 release. 

Please remove any import of **tensorflow.python.keras** and use the public API with **from tensorflow import keras** or **import tensorflow as tf; tf.keras.**

I tried to execute the mentioned code on tensorflow **v2.13** by using  below imports and it was executed without any issues.

```
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras import Sequential
from tensorflow.keras.activations import sigmoid
```

Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/6975de68760fead5d9b255261812163d/untitled.ipynb). 
https://github.com/tensorflow/tensorflow/releases

Thank you! @tilakrayal
Got it! 

Worked with the public API and **from tensorflow import keras**

Thanks ;) 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/61215">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/61215">No</a>
 > @samuelsennev, **tensorflow/python/keras** code is a legacy copy of Keras since the TensorFlow v2.7 release, and will be deleted in the v2.12 release.
> 
> Please remove any import of **tensorflow.python.keras** and use the public API with **from tensorflow import keras** or **import tensorflow as tf; tf.keras.**
> 
> I tried to execute the mentioned code on tensorflow **v2.13** by using below imports and it was executed without any issues.
> 
> ```
> from tensorflow.keras.layers import Dense, Input
> from tensorflow.keras import Sequential
> from tensorflow.keras.activations import sigmoid
> ```
> 
> Kindly find the gist of it [here](https://colab.research.google.com/gist/tilakrayal/6975de68760fead5d9b255261812163d/untitled.ipynb). https://github.com/tensorflow/tensorflow/releases
> 
> Thank you!

it does works!
but after i change the imports code, the IDE(vs code) cannot recognize any type under keras， is there any way to resolve it? https://stackoverflow.com/a/77733620/13086128
### Issue type

Bug

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

No

### Source

source

### TensorFlow version

2.13

### Custom code

No

### OS platform and distribution

_No response_

### Mobile device

_No response_

### Python version

3.10.9

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

I'm new to machine learning and I was setting up this network with just one layer, with only one neuron inside it, just to see how it works. Setting up went fine. The error occured when I asked it to predict.

I'm not sure what exactly happend, but apparently, a non existent attribute (`input_lib.DistributedDatasetInterface`) was passed to `isinstance()` in the file: ...\site-packages\tensorflow\python\keras\engine\data_adapter.py (line 1699).

I've replaced by the wrong one by the one suggested and worked as expected.

### Standalone code to reproduce the issue

```shell
import numpy as np
import tensorflow as tf
from tensorflow.python.keras.layers import Dense, Input
from tensorflow.python.keras import Sequential
from tensorflow.python.keras.activations import sigmoid

import logging
logging.getLogger("tensorflow").setLevel(logging.ERROR)
tf.autograph.set_verbosity(0)

X_train = np.array([0., 1, 2, 3, 4, 5], dtype=np.float32).reshape(-1,1)
Y_train = np.array([0,  0, 0, 1, 1, 1], dtype=np.float32).reshape(-1,1)

model = Sequential([
    Input(shape=(1,)),
    Dense(1, activation=sigmoid, name = "L1")
])
model.summary()

# Setting the weights and bias of the neuron
logistic_layer = model.get_layer('L1')
set_w = np.array([[2]])
set_b = np.array([-4.5])
logistic_layer.set_weights([set_w, set_b])

# Performance test
a1 = model.predict(X_train[0].reshape(1,1)) # this line caused the error
print(a1)
alog = sigmoid(np.dot(set_w,X_train[0].reshape(1,1)) + set_b)
print(alog)
```


### Relevant log output

```shell
...\site-packages\tensorflow\python\keras\engine\data_adapter.py", line 1699, in _is_distributed_dataset
    return isinstance(ds, input_lib.DistributedDatasetInterface)
AttributeError: module 'tensorflow.python.distribute.input_lib' has no attribute 'DistributedDatasetInterface'. Did you mean: 'DistributedDatasetSpec'?
```
