AttributeError: module 'tensorflow.python.distribute.input_lib' has no attribute 'DistributedDatasetInterface'
Hi @PreWisdom ,

By looking at attribute error, I would like to suggest to check the issue with TF2.12V and let us know the outcome.It seems there are shiftings in Tf2.12v and Tf2.13v. 

With Tf2.13V the path `tensorflow.python.distribute.input_lib` don't have the class `DistributedDatasetInterface` but in Tf2.12 it does.
 > Hi @PreWisdom ,
> 
> By looking at attribute error, I would like to suggest to check the issue with TF2.12V and let us know the outcome.It seems there are shiftings in Tf2.12v and Tf2.13v.
> 
> With Tf2.13V the path `tensorflow.python.distribute.input_lib` don't have the class `DistributedDatasetInterface` but in Tf2.12 it does.

thanks for reply, I'm gonna change version to 2.12 and see what happen. Hi @PreWisdom ,

Could you please check the issue with tf-nightly. Actually there has been some changes. Now Keras has became a Multi backend support (for TF,Pytorch and JAX). All the tf.keras module i.e Keras with TF backend has been moved to new repo i.e [tf-keras](https://github.com/keras-team/tf-keras).

I can see in tf-keras the code is different than in tf.keras module. I want to cross check with you with both tf-nightly and keras-nightly and confirm outcome ? > Hi @PreWisdom ,
> 
> Could you please check the issue with tf-nightly. Actually there has been some changes. Now Keras has became a Multi backend support (for TF,Pytorch and JAX). All the tf.keras module i.e Keras with TF backend has been moved to new repo i.e [tf-keras](https://github.com/keras-team/tf-keras).
> 
> I can see in tf-keras the code is different than in tf.keras module. I want to cross check with you with both tf-nightly and keras-nightly and confirm outcome ?

sure, there are still has some problems in my code, looks like it's due to a package name change. I'll keep on tracking these bugs. 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?
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### Issue type

Bug

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

Yes

### Source

source

### TensorFlow version

2.13.0

### Custom code

Yes

### OS platform and distribution

Linux Ubuntu 22.04.3

### Mobile device

_No response_

### Python version

2.13.0

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

OS : Ubuntu 22.04.3
Software: Pycharm
files: LogisticRegression_withTensorflow.ipynb

I dont know what happen, it just work yesterday
when I run this code:
`model.fit(X_train, y_train, epochs=150)`


### Standalone code to reproduce the issue

```shell
# import library
import numpy as np
import tensorflow as tf
from tensorflow.python.keras import Sequential
from tensorflow.python.keras.layers import Dense
from tensorflow.python.keras.losses import BinaryCrossentropy
print(tf.__version__)
# 2.13.0
# import data
X = []
y = []
with open('../../Part1/Week2/data/ex2data1.txt') as file:
# with open('/home/wisdom/vs_code_repository/Python/AndrewNG_ML/Part1/Week2/data/ex2data1.txt', 'r') as file:
    for lines in file:
        colums = lines.strip().split(',')
        X.append([float(colums[0]), float(colums[1])])
        y.append(float(colums[2]))
X = np.array(X)
y = np.array(y)
# normalization
X_mean = np.mean(X, axis=0)
X_max = np.max(X, axis=0)
X_min = np.min(X, axis=0)
X = (X - X_mean) / (X_max - X_min)

# split data into training_set and testing_set
X_train = X[:80]
y_train = y[:80]
X_test = X[80:]
y_test = y[80:]
model = Sequential([Dense(units=32, activation='sigmoid'),
                    Dense(units=16, activation='sigmoid'),
                    Dense(units=1, activation='sigmoid')])
model.compile(loss=BinaryCrossentropy())
model.fit(X_train, y_train, epochs=150) # bug appears this line
```


### Relevant log output

```shell
AttributeError                            Traceback (most recent call last)
Cell In[13], line 1
----> 1 model.fit(X_train, y_train, epochs=150)

File /usr/local/lib/python3.10/dist-packages/tensorflow/python/keras/engine/training.py:1138, in Model.fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
   1132   self._cluster_coordinator = cluster_coordinator.ClusterCoordinator(
   1133       self.distribute_strategy)
   1135 with self.distribute_strategy.scope(), \
   1136      training_utils.RespectCompiledTrainableState(self):
   1137   # Creates a `tf.data.Dataset` and handles batch and epoch iteration.
-> 1138   data_handler = data_adapter.get_data_handler(
   1139       x=x,
   1140       y=y,
   1141       sample_weight=sample_weight,
   1142       batch_size=batch_size,
   1143       steps_per_epoch=steps_per_epoch,
   1144       initial_epoch=initial_epoch,
   1145       epochs=epochs,
   1146       shuffle=shuffle,
   1147       class_weight=class_weight,
   1148       max_queue_size=max_queue_size,
   1149       workers=workers,
   1150       use_multiprocessing=use_multiprocessing,
   1151       model=self,
   1152       steps_per_execution=self._steps_per_execution)
   1154   # Container that configures and calls `tf.keras.Callback`s.
   1155   if not isinstance(callbacks, callbacks_module.CallbackList):

File /usr/local/lib/python3.10/dist-packages/tensorflow/python/keras/engine/data_adapter.py:1398, in get_data_handler(*args, **kwargs)
   1396 if getattr(kwargs["model"], "_cluster_coordinator", None):
   1397   return _ClusterCoordinatorDataHandler(*args, **kwargs)
-> 1398 return DataHandler(*args, **kwargs)

File /usr/local/lib/python3.10/dist-packages/tensorflow/python/keras/engine/data_adapter.py:1152, in DataHandler.__init__(self, x, y, sample_weight, batch_size, steps_per_epoch, initial_epoch, epochs, shuffle, class_weight, max_queue_size, workers, use_multiprocessing, model, steps_per_execution, distribute)
   1149   self._steps_per_execution = steps_per_execution
   1150   self._steps_per_execution_value = steps_per_execution.numpy().item()
-> 1152 adapter_cls = select_data_adapter(x, y)
   1153 self._adapter = adapter_cls(
   1154     x,
   1155     y,
   (...)
   1164     distribution_strategy=distribute_lib.get_strategy(),
   1165     model=model)
   1167 strategy = distribute_lib.get_strategy()

File /usr/local/lib/python3.10/dist-packages/tensorflow/python/keras/engine/data_adapter.py:988, in select_data_adapter(x, y)
    986 def select_data_adapter(x, y):
    987   """Selects a data adapter than can handle a given x and y."""
--> 988   adapter_cls = [cls for cls in ALL_ADAPTER_CLS if cls.can_handle(x, y)]
    989   if not adapter_cls:
    990     # TODO(scottzhu): This should be a less implementation-specific error.
    991     raise ValueError(
    992         "Failed to find data adapter that can handle "
    993         "input: {}, {}".format(
    994             _type_name(x), _type_name(y)))

File /usr/local/lib/python3.10/dist-packages/tensorflow/python/keras/engine/data_adapter.py:988, in <listcomp>(.0)
    986 def select_data_adapter(x, y):
    987   """Selects a data adapter than can handle a given x and y."""
--> 988   adapter_cls = [cls for cls in ALL_ADAPTER_CLS if cls.can_handle(x, y)]
    989   if not adapter_cls:
    990     # TODO(scottzhu): This should be a less implementation-specific error.
    991     raise ValueError(
    992         "Failed to find data adapter that can handle "
    993         "input: {}, {}".format(
    994             _type_name(x), _type_name(y)))

File /usr/local/lib/python3.10/dist-packages/tensorflow/python/keras/engine/data_adapter.py:707, in DatasetAdapter.can_handle(x, y)
    704 @staticmethod
    705 def can_handle(x, y=None):
    706   return (isinstance(x, (data_types.DatasetV1, data_types.DatasetV2)) or
--> 707           _is_distributed_dataset(x))

File /usr/local/lib/python3.10/dist-packages/tensorflow/python/keras/engine/data_adapter.py:1699, in _is_distributed_dataset(ds)
   1698 def _is_distributed_dataset(ds):
-> 1699   return isinstance(ds, input_lib.DistributedDatasetInterface)

AttributeError: module 'tensorflow.python.distribute.input_lib' has no attribute 'DistributedDatasetInterface'
```
