TensorFlow ImportError: cannot import name 'dtensor'

Question

I'm facing an issue while trying to run a TensorFlow program on my computer. I've installed Python 3.8 and TensorFlow, and I don't have a GPU.

When I import TensorFlow with the command import tensorflow as tf, I receive a warning due to the absence of a GPU, which is expected.

However, when I try to execute a program that uses TensorFlow, I encounter an error that I'm struggling to resolve. The code looks like this:

#!/usr/bin/env python3
import tensorflow.compat.v1 as tf
tf.disable_eager_execution()

def create_layer(prev, n, activation):
    w_init = tf.keras.initializers.VarianceScaling(mode='fan_avg')
    name = activation.__name__.capitalize()

    layer = tf.layers.dense(
            n,
            activation=activation,
            kernel_initializer=w_init,
            bias_initializer=tf.compat.v1.zeros_initializer(),
            name=layer,
    )

    return layer(prev)

create_placeholders = __import__('0-create_placeholders').create_placeholders
x, y = create_placeholders(784, 10)
l = create_layer(x, 256, tf.nn.tanh)
print(l)

Upon running this script, I encounter the following error:

2024-01-16 21:38:39.626120: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2024-01-16 21:38:39.626799: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Traceback (most recent call last):
Traceback (most recent call last):
  File ".\1-create_layer.py", line 45, in <module>
    l = create_layer(x, 256, tf.nn.tanh)
  File ".\1-create_layer.py", line 29, in create_layer
    w_init = tf.keras.initializers.VarianceScaling(mode='fan_avg')
  File "C:\Python38\lib\site-packages\tensorflow\python\util\lazy_loader.py", line 62, in __getattr__
    module = self._load()
  File "C:\Python38\lib\site-packages\tensorflow\python\util\lazy_loader.py", line 45, in _load
    module = importlib.import_module(self.__name__)
  File "C:\Python38\lib\importlib\__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1014, in _gcd_import
  File "<frozen importlib._bootstrap>", line 991, in _find_and_load
  File "<frozen importlib._bootstrap>", line 961, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "<frozen importlib._bootstrap>", line 1014, in _gcd_import
  File "<frozen importlib._bootstrap>", line 991, in _find_and_load
  File "<frozen importlib._bootstrap>", line 961, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "<frozen importlib._bootstrap>", line 1014, in _gcd_import
  File "<frozen importlib._bootstrap>", line 991, in _find_and_load
  File "<frozen importlib._bootstrap>", line 961, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "<frozen importlib._bootstrap>", line 1014, in _gcd_import
  File "<frozen importlib._bootstrap>", line 991, in _find_and_load
  File "<frozen importlib._bootstrap>", line 975, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 671, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 783, in exec_module
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "C:\Python38\lib\site-packages\keras\__init__.py", line 3, in <module>
    from keras import __internal__
  File "C:\Python38\lib\site-packages\keras\__internal__\__init__.py", line 3, in <module>
    from keras.__internal__ import backend
  File "C:\Python38\lib\site-packages\keras\__internal__\backend\__init__.py", line 3, in <module>
    from keras.src.backend import _initialize_variables as initialize_variables
  File "C:\Python38\lib\site-packages\keras\src\__init__.py", line 21, in <module>
    from keras.src import applications
  File "C:\Python38\lib\site-packages\keras\src\applications\__init__.py", line 18, in <module>
    from keras.src.applications.convnext import ConvNeXtBase
  File "C:\Python38\lib\site-packages\keras\src\applications\convnext.py", line 28, in <module>
    from keras.src import backend
  File "C:\Python38\lib\site-packages\keras\src\backend.py", line 34, in <module>
    from keras.src.dtensor import dtensor_api as dtensor
  File "C:\Python38\lib\site-packages\keras\src\dtensor\__init__.py", line 18, in <module>
    from tensorflow.compat.v2.experimental import dtensor as dtensor_api
ImportError: cannot import name 'dtensor' from 'tensorflow.compat.v2.experimental' (C:\Python38\lib\site-packages\tensorflow\_api\v2\compat\v2\experimental\__init__.py)

I don't understand the source of this error and would appreciate any help in resolving it. I suspect it might be related to the TensorFlow and Keras versions or the absence of GPU support.

At the beginning, I ran my code in a Vagrant VM environment, believing that the issue was related to Vagrant. However, upon testing it locally, I encountered the same error. (I am constrained to using a specific version of TensorFlow for a school task.)

Answer 1

The error you're facing indicates that there is an issue with importing a module called dtensor from TensorFlow's experimental compatibility module.

So there are some steps we need to check:-

Check TensorFlow Version:- First we need to check that we are using a compatible version of tensorflow You can check the TensorFlow version by running import tensorflow as tf followed by print(tf.__version__).

If you are not using the updated version then use this command to update it into the latest version pip install--upgrade tensorflow.

Ensure that TensorFlow is installed correctly and all dependencies are satisfied. Sometimes, errors can occur due to incomplete or corrupted installations.

Check if your code is compatible with the version of TensorFlow you have installed.because some time code written for older versions may not work as expected with newer versions due to changes in APIs or module structures.