pywrap
In order to expedite the trouble-shooting process, please provide all the dependencies to reproduce the issue reported here. I have faced a different [issue](https://colab.research.google.com/gist/sushreebarsa/840f8f7a4d9d45d74db62b848ec264e5/62612.ipynb) for replicating the same as reported,please have a look. 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?
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### Issue type

Support

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

No

### Source

source

### TensorFlow version

2.15

### Custom code

Yes

### OS platform and distribution

windows 11 64 biit

### Mobile device

windows 11

### Python version

3.9

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?


### Standalone code to reproduce the issue

```shell
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import tensorflow as tf
from tensorflow.python import pywrap_tensorflow
from tensorflow.keras import layers
from tensorflow.keras.preprocessing.image import ImageDataGenerator

# Load the pre-trained model
base_model = tf.keras.applications.InceptionV3(include_top=False, weights='imagenet')

# Freeze the initial layers of the pre-trained model
for layer in base_model.layers:
    layer.trainable = False

# Add new layers for fine-tuning
x = base_model.output
x = layers.GlobalAveragePooling2D()(x)
x = layers.Dense(128, activation='relu')(x)
x = layers.Dense(64, activation='relu')(x)
predictions = layers.Dense(3, activation='softmax')(x)

# Create the fine-tuned model
model = tf.keras.Model(inputs=base_model.input, outputs=predictions)

# Compile the model
model.compile(optimizer='adam',
              loss='categorical_crossentropy',
              metrics=['accuracy'])

# Prepare the data generators
train_datagen = ImageDataGenerator(rescale=1./255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True)
val_datagen = ImageDataGenerator(rescale=1./255)

train_generator = train_datagen.flow_from_directory(
    'training_data',
    target_size=(224, 224),
    batch_size=32,
    class_mode='categorical')

validation_generator = val_datagen.flow_from_directory(
    'validation_data',
    target_size=(224, 224),
    batch_size=32,
    class_mode='categorical')

# Train the model
history = model.fit(
    train_generator,
    steps_per_epoch=len(train_generator),
    epochs=10,
    validation_data=validation_generator,
    validation_steps=len(validation_generator))

# Save the trained model
model.save('ceramic_classifier.h5')
```


### Relevant log output

```shell
Traceback (most recent call last):

  File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\IPython\core\interactiveshell.py:3550 in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)

  Cell In[8], line 3
    import tensorflow as tf

  File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\tensorflow\__init__.py:24
    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import

  File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\tensorflow\python\__init__.py:49
    from tensorflow.python import pywrap_tensorflow

  File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\tensorflow\python\pywrap_tensorflow.py:58
    from tensorflow.python.pywrap_tensorflow_internal import *

  File ~\AppData\Local\Programs\Python\Python312\Lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py:114
    def TFE_ContextOptionsSetAsync(arg1, async):
                                         ^
SyntaxError: invalid syntax
```

it always show when i run the code