When I install tensorflow using conda, I have  the problem saying that AttributeError: module 'numpy' has no attribute 'object'. `np.object` was a deprecated alias for the builtin `object`. To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:     https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
@ABtwo,
The error you are facing **module 'numpy' has no attribute 'object'** is due to numpy version. Could you please try to install `pip install numpy==1.23.4`. Also you are trying to install tensorflow v2.6 which is older and try to follow the compatible test build configurations from the official [document](https://www.tensorflow.org/install/source_windows#gpu). Please try to update to the latest stable version. Thank you! @tilakrayal I have the same issue on Windows. According to the [compatible](https://www.tensorflow.org/install/source_windows#gpu) versions table cuda 12.3 isn’t supported in the latest windows release. Is there an issue tracking the update to 12.3 cuda for windows?  @skidrw,
AFAIK there is no such request for the 12.3 CUDA for Windows environment. There might be a chance that the CUDA version 12.3 will be compatible in the latest tensorflow versions. Could you please feel free to raise the new feature request from [here](https://github.com/tensorflow/tensorflow/issues/new/choose) for the same. 

Also GPU support on native-Windows is only available for 2.10 or earlier versions, starting in TF 2.11, CUDA build is not supported for Windows. For using TensorFlow GPU on Windows, you will need to build/install TensorFlow in WSL2 or use tensorflow-cpu with TensorFlow-DirectML-Plugin

Thank you! @tilakrayal ,
Thank you so much for answering my question, 
Are you the official technician? I have tried this "pip install numpy==1.23.4" command. 
It prompted me "Successfully installed numpy-1.23.4" but there occurred incompatible errors  like that  
"ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
tensorflow 2.6.0 requires clang~=5.0, which is not installed.
tensorflow 2.6.0 requires keras>=2.4.0, which is not installed.
tensorboard 2.6.0 requires google-auth<2,>=1.6.3, but you have google-auth 2.22.0 which is incompatible.
tensorflow 2.6.0 requires absl-py~=0.10, but you have absl-py 1.4.0 which is incompatible.
tensorflow 2.6.0 requires flatbuffers~=1.12, but you have flatbuffers 20210226132247 which is incompatible."

So I tried "conda install numpy==1.23.4"  It may installed the compatible packages automatically and there were  no incompatible errors. then I tried to import tensorflow,It worked correctly

Before I saw your answer, I have tried to correct the deprecated errors by changing the "np.object" to "object ,"np.bool" to"bool" as it prompted me in the corresponding files. It may be worked, I have imported tensorflow correctly, and run the command "print(tf.__version__)" and "print(tf.config.list_physical_devices('GPU'))". they all made the correct output.

What's more , I want to say when I try to install tensorflow 2.10  using "conda  create -n tf-gpu tensorflow-gpu==2.10",It prompts me that 
"Channels:
 - defaults
Platform: win-64
Collecting package metadata (repodata.json): done
Solving environment: failed

PackagesNotFoundError: The following packages are not available from current channels:

  - tensorflow-gpu==2.10

Current channels:

  - defaults

To search for alternate channels that may provide the conda package you're
looking for, navigate to

    https://anaconda.org

and use the search bar at the top of the page."

Should I try "pip install tensorflow-gpu==2.10" command in the virtual environment?  Please give me some advice.

Thanks again for answering me


 @ABtwo,
Yes, you can try to install the required tensorflow version using `pip install tensorflow-gpu==2.10` in the new virtual environment. GPU support on native-Windows is only available for 2.10 or earlier versions, starting in TF 2.11, CUDA build is not supported for Windows. For using TensorFlow GPU on Windows, you will need to build/install TensorFlow in WSL2 or use tensorflow-cpu with TensorFlow-DirectML-Plugin. 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/62832">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/62832">No</a>

### Issue type

Bug

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

Yes

### Source

source

### TensorFlow version

tensorflow-GPU 2.6

### Custom code

Yes

### OS platform and distribution

Windows10

### Mobile device

_No response_

### Python version

3.9

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

12.3 cudnn version :8.9.6

### GPU model and memory

_No response_

### Current behavior?

When I Install tensorflow-gpu by conda ,  I created the tf-gpu environment, but when I  run this instraction"import tensorflow as tf" in python I met this problem  AttributeError: module 'numpy' has no attribute 'object'.
`np.object` was a deprecated alias for the builtin `object`. To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

Then I tried to correct the problem by uninstall my numpy which version is 1.26.3  and install the numpy=1.19 , there was another problem like this 
"  error: subprocess-exited-with-error

  × Preparing metadata (pyproject.toml) did not run successfully.
  │ exit code: 1
  ╰─> [90 lines of output]
      Running from numpy source directory.
      <string>:460: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
      C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py:73: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
        required_version = LooseVersion('0.29.14')
      C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py:75: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
        if LooseVersion(cython_version) < required_version:
      performance hint: _common.pyx:275:19: Exception check after calling 'random_func' will always require the GIL to be acquired. Declare 'random_func' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:299:19: Exception check after calling 'random_func' will always require the GIL to be acquired. Declare 'random_func' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:322:50: Exception check after calling 'random_func' will always require the GIL to be acquired. Declare 'random_func' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:426:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:465:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:509:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:592:36: Exception check after calling 'f0' will always require the GIL to be acquired. Declare 'f0' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:596:36: Exception check after calling 'f1' will always require the GIL to be acquired. Declare 'f1' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:600:36: Exception check after calling 'f2' will always require the GIL to be acquired. Declare 'f2' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:604:36: Exception check after calling 'f3' will always require the GIL to be acquired. Declare 'f3' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:638:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:675:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:712:63: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:754:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:785:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:903:40: Exception check after calling 'f0' will always require the GIL to be acquired. Declare 'f0' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:907:40: Exception check after calling 'fd' will always require the GIL to be acquired. Declare 'fd' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:911:41: Exception check after calling 'fdd' will always require the GIL to be acquired. Declare 'fdd' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:916:40: Exception check after calling 'fi' will always require the GIL to be acquired. Declare 'fi' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:920:41: Exception check after calling 'fdi' will always require the GIL to be acquired. Declare 'fdi' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:924:38: Exception check after calling 'fiii' will always require the GIL to be acquired. Declare 'fiii' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:960:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:1002:32: Exception check after calling 'f1' will always require the GIL to be acquired. Declare 'f1' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _generator.pyx:706:41: Exception check after calling '_shuffle_int' will always require the GIL to be acquired.
      Possible solutions:
          1. Declare '_shuffle_int' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
          2. Use an 'int' return type on '_shuffle_int' to allow an error code to be returned.
      performance hint: _generator.pyx:735:45: Exception check after calling '_shuffle_int' will always require the GIL to be acquired.
      Possible solutions:
          1. Declare '_shuffle_int' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
          2. Use an 'int' return type on '_shuffle_int' to allow an error code to be returned.

      Error compiling Cython file:
      ------------------------------------------------------------
      ...
              for i in range(1, RK_STATE_LEN):
                  self.rng_state.key[i] = val[i]
              self.rng_state.pos = i

              self._bitgen.state = &self.rng_state
              self._bitgen.next_uint64 = &mt19937_uint64
                                         ^
      ------------------------------------------------------------

      _mt19937.pyx:138:35: Cannot assign type 'uint64_t (*)(void *) except? -1 nogil' to 'uint64_t (*)(void *) noexcept nogil'. Exception values are incompatible. Suggest adding 'noexcept' to type 'uint64_t (void *) except? -1 nogil'.
      Processing numpy/random\_bounded_integers.pxd.in
      Processing numpy/random\bit_generator.pyx
      Processing numpy/random\mtrand.pyx
      Processing numpy/random\_bounded_integers.pyx.in
      Processing numpy/random\_common.pyx
      Processing numpy/random\_generator.pyx
      Processing numpy/random\_mt19937.pyx
      Traceback (most recent call last):
        File "C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py", line 235, in <module>
          main()
        File "C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py", line 231, in main
          find_process_files(root_dir)
        File "C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py", line 222, in find_process_files
          process(root_dir, fromfile, tofile, function, hash_db)
        File "C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py", line 188, in process
          processor_function(fromfile, tofile)
        File "C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py", line 77, in process_pyx
          subprocess.check_call(
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\subprocess.py", line 373, in check_call
          raise CalledProcessError(retcode, cmd)
      subprocess.CalledProcessError: Command '['D:\\WorkSpace\\Anaconda_WorkSpace\\envs\\tf-gpu\\python.exe', '-m', 'cython', '-3', '--fast-fail', '-o', '_mt19937.c', '_mt19937.pyx']' returned non-zero exit status 1.
      Cythonizing sources
      Traceback (most recent call last):
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 353, in <module>
          main()
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 335, in main
          json_out['return_val'] = hook(**hook_input['kwargs'])
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 149, in prepare_metadata_for_build_wheel
          return hook(metadata_directory, config_settings)
        File "C:\Users\dell\AppData\Local\Temp\pip-build-env-yguajv_e\overlay\Lib\site-packages\setuptools\build_meta.py", line 366, in prepare_metadata_for_build_wheel
          self.run_setup()
        File "C:\Users\dell\AppData\Local\Temp\pip-build-env-yguajv_e\overlay\Lib\site-packages\setuptools\build_meta.py", line 480, in run_setup
          super(_BuildMetaLegacyBackend, self).run_setup(setup_script=setup_script)
        File "C:\Users\dell\AppData\Local\Temp\pip-build-env-yguajv_e\overlay\Lib\site-packages\setuptools\build_meta.py", line 311, in run_setup
          exec(code, locals())
        File "<string>", line 489, in <module>
        File "<string>", line 469, in setup_package
        File "<string>", line 274, in generate_cython
      RuntimeError: Running cythonize failed!
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details."


### Standalone code to reproduce the issue

```shell
conda create -n tf-gpu tensorflow-gpu
conda activate tf-gpu

import tensorflow as tf
```


### Relevant log output

```shell
Python 3.9.18 (main, Sep 11 2023, 13:30:38) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\dtypes.py:585: FutureWarning: In the future `np.object` will be defined as the corresponding NumPy scalar.
  np.object,
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\__init__.py", line 41, in <module>
    from tensorflow.python.tools import module_util as _module_util
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\__init__.py", line 46, in <module>
    from tensorflow.python import data
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\__init__.py", line 25, in <module>
    from tensorflow.python.data import experimental
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\__init__.py", line 97, in <module>
    from tensorflow.python.data.experimental import service
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\service\__init__.py", line 353, in <module>
    from tensorflow.python.data.experimental.ops.data_service_ops import distribute
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\ops\data_service_ops.py", line 26, in <module>
    from tensorflow.python.data.experimental.ops import compression_ops
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\ops\compression_ops.py", line 20, in <module>
    from tensorflow.python.data.util import structure
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\util\structure.py", line 26, in <module>
    from tensorflow.python.data.util import nest
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\util\nest.py", line 40, in <module>
    from tensorflow.python.framework import sparse_tensor as _sparse_tensor
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\sparse_tensor.py", line 28, in <module>
    from tensorflow.python.framework import constant_op
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\constant_op.py", line 29, in <module>
    from tensorflow.python.eager import execute
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\eager\execute.py", line 27, in <module>
    from tensorflow.python.framework import dtypes
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\dtypes.py", line 585, in <module>
    np.object,
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\numpy\__init__.py", line 324, in __getattr__
    raise AttributeError(__former_attrs__[attr])
AttributeError: module 'numpy' has no attribute 'object'.
`np.object` was a deprecated alias for the builtin `object`. To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
>>> import tensorflow as tf
D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\dtypes.py:627: FutureWarning: In the future `np.object` will be defined as the corresponding NumPy scalar.
  np.object,
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\__init__.py", line 41, in <module>
    from tensorflow.python.tools import module_util as _module_util
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\__init__.py", line 46, in <module>
    from tensorflow.python import data
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\__init__.py", line 25, in <module>
    from tensorflow.python.data import experimental
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\__init__.py", line 97, in <module>
    from tensorflow.python.data.experimental import service
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\service\__init__.py", line 353, in <module>
    from tensorflow.python.data.experimental.ops.data_service_ops import distribute
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\ops\data_service_ops.py", line 26, in <module>
    from tensorflow.python.data.experimental.ops import compression_ops
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\ops\compression_ops.py", line 20, in <module>
    from tensorflow.python.data.util import structure
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\util\structure.py", line 26, in <module>
    from tensorflow.python.data.util import nest
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\util\nest.py", line 40, in <module>
    from tensorflow.python.framework import sparse_tensor as _sparse_tensor
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\sparse_tensor.py", line 28, in <module>
    from tensorflow.python.framework import constant_op
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\constant_op.py", line 29, in <module>
    from tensorflow.python.eager import execute
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\eager\execute.py", line 27, in <module>
    from tensorflow.python.framework import dtypes
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\dtypes.py", line 627, in <module>
    np.object,
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\numpy\__init__.py", line 324, in __getattr__
    raise AttributeError(__former_attrs__[attr])
AttributeError: module 'numpy' has no attribute 'object'.
`np.object` was a deprecated alias for the builtin `object`. To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
>>> import tensorflow as tf
D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\dtypes.py:637: FutureWarning: In the future `np.bool` will be defined as the corresponding NumPy scalar.
  np.bool,
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\__init__.py", line 41, in <module>
    from tensorflow.python.tools import module_util as _module_util
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\__init__.py", line 46, in <module>
    from tensorflow.python import data
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\__init__.py", line 25, in <module>
    from tensorflow.python.data import experimental
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\__init__.py", line 97, in <module>
    from tensorflow.python.data.experimental import service
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\service\__init__.py", line 353, in <module>
    from tensorflow.python.data.experimental.ops.data_service_ops import distribute
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\ops\data_service_ops.py", line 26, in <module>
    from tensorflow.python.data.experimental.ops import compression_ops
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\experimental\ops\compression_ops.py", line 20, in <module>
    from tensorflow.python.data.util import structure
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\util\structure.py", line 26, in <module>
    from tensorflow.python.data.util import nest
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\data\util\nest.py", line 40, in <module>
    from tensorflow.python.framework import sparse_tensor as _sparse_tensor
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\sparse_tensor.py", line 28, in <module>
    from tensorflow.python.framework import constant_op
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\constant_op.py", line 29, in <module>
    from tensorflow.python.eager import execute
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\eager\execute.py", line 27, in <module>
    from tensorflow.python.framework import dtypes
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\tensorflow\python\framework\dtypes.py", line 637, in <module>
    np.bool,
  File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\numpy\__init__.py", line 324, in __getattr__
    raise AttributeError(__former_attrs__[attr])
AttributeError: module 'numpy' has no attribute 'bool'.
`np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
>>> pip uninstall numpy
  File "<stdin>", line 1
    pip uninstall numpy
        ^
SyntaxError: invalid syntax
>>> exit()

(tf-gpu) C:\Users\dell>pip uninstall numpy
Found existing installation: numpy 1.26.3
Uninstalling numpy-1.26.3:
  Would remove:
    d:\workspace\anaconda_workspace\envs\tf-gpu\lib\site-packages\numpy-1.26.3.dist-info\*
    d:\workspace\anaconda_workspace\envs\tf-gpu\lib\site-packages\numpy\*
    d:\workspace\anaconda_workspace\envs\tf-gpu\scripts\f2py-script.py
    d:\workspace\anaconda_workspace\envs\tf-gpu\scripts\f2py.exe
Proceed (Y/n)? y
  Successfully uninstalled numpy-1.26.3

(tf-gpu) C:\Users\dell>pip install -U numpy==1.19
Collecting numpy==1.19
  Using cached numpy-1.19.0.zip (7.3 MB)
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
  Preparing metadata (pyproject.toml) ... error
  error: subprocess-exited-with-error

  × Preparing metadata (pyproject.toml) did not run successfully.
  │ exit code: 1
  ╰─> [90 lines of output]
      Running from numpy source directory.
      <string>:460: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
      C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py:73: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
        required_version = LooseVersion('0.29.14')
      C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py:75: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
        if LooseVersion(cython_version) < required_version:
      performance hint: _common.pyx:275:19: Exception check after calling 'random_func' will always require the GIL to be acquired. Declare 'random_func' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:299:19: Exception check after calling 'random_func' will always require the GIL to be acquired. Declare 'random_func' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:322:50: Exception check after calling 'random_func' will always require the GIL to be acquired. Declare 'random_func' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:426:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:465:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:509:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:592:36: Exception check after calling 'f0' will always require the GIL to be acquired. Declare 'f0' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:596:36: Exception check after calling 'f1' will always require the GIL to be acquired. Declare 'f1' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:600:36: Exception check after calling 'f2' will always require the GIL to be acquired. Declare 'f2' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:604:36: Exception check after calling 'f3' will always require the GIL to be acquired. Declare 'f3' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:638:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:675:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:712:63: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:754:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:785:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:903:40: Exception check after calling 'f0' will always require the GIL to be acquired. Declare 'f0' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:907:40: Exception check after calling 'fd' will always require the GIL to be acquired. Declare 'fd' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:911:41: Exception check after calling 'fdd' will always require the GIL to be acquired. Declare 'fdd' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:916:40: Exception check after calling 'fi' will always require the GIL to be acquired. Declare 'fi' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:920:41: Exception check after calling 'fdi' will always require the GIL to be acquired. Declare 'fdi' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:924:38: Exception check after calling 'fiii' will always require the GIL to be acquired. Declare 'fiii' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:960:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:1002:32: Exception check after calling 'f1' will always require the GIL to be acquired. Declare 'f1' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _generator.pyx:706:41: Exception check after calling '_shuffle_int' will always require the GIL to be acquired.
      Possible solutions:
          1. Declare '_shuffle_int' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
          2. Use an 'int' return type on '_shuffle_int' to allow an error code to be returned.
      performance hint: _generator.pyx:735:45: Exception check after calling '_shuffle_int' will always require the GIL to be acquired.
      Possible solutions:
          1. Declare '_shuffle_int' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
          2. Use an 'int' return type on '_shuffle_int' to allow an error code to be returned.

      Error compiling Cython file:
      ------------------------------------------------------------
      ...
              for i in range(1, RK_STATE_LEN):
                  self.rng_state.key[i] = val[i]
              self.rng_state.pos = i

              self._bitgen.state = &self.rng_state
              self._bitgen.next_uint64 = &mt19937_uint64
                                         ^
      ------------------------------------------------------------

      _mt19937.pyx:138:35: Cannot assign type 'uint64_t (*)(void *) except? -1 nogil' to 'uint64_t (*)(void *) noexcept nogil'. Exception values are incompatible. Suggest adding 'noexcept' to type 'uint64_t (void *) except? -1 nogil'.
      Processing numpy/random\_bounded_integers.pxd.in
      Processing numpy/random\bit_generator.pyx
      Processing numpy/random\mtrand.pyx
      Processing numpy/random\_bounded_integers.pyx.in
      Processing numpy/random\_common.pyx
      Processing numpy/random\_generator.pyx
      Processing numpy/random\_mt19937.pyx
      Traceback (most recent call last):
        File "C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py", line 235, in <module>
          main()
        File "C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py", line 231, in main
          find_process_files(root_dir)
        File "C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py", line 222, in find_process_files
          process(root_dir, fromfile, tofile, function, hash_db)
        File "C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py", line 188, in process
          processor_function(fromfile, tofile)
        File "C:\Users\dell\AppData\Local\Temp\pip-install-_lwzhmzj\numpy_4bbed4470a5a4d1aa30ccee14c45028a\tools\cythonize.py", line 77, in process_pyx
          subprocess.check_call(
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\subprocess.py", line 373, in check_call
          raise CalledProcessError(retcode, cmd)
      subprocess.CalledProcessError: Command '['D:\\WorkSpace\\Anaconda_WorkSpace\\envs\\tf-gpu\\python.exe', '-m', 'cython', '-3', '--fast-fail', '-o', '_mt19937.c', '_mt19937.pyx']' returned non-zero exit status 1.
      Cythonizing sources
      Traceback (most recent call last):
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 353, in <module>
          main()
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 335, in main
          json_out['return_val'] = hook(**hook_input['kwargs'])
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 149, in prepare_metadata_for_build_wheel
          return hook(metadata_directory, config_settings)
        File "C:\Users\dell\AppData\Local\Temp\pip-build-env-yguajv_e\overlay\Lib\site-packages\setuptools\build_meta.py", line 366, in prepare_metadata_for_build_wheel
          self.run_setup()
        File "C:\Users\dell\AppData\Local\Temp\pip-build-env-yguajv_e\overlay\Lib\site-packages\setuptools\build_meta.py", line 480, in run_setup
          super(_BuildMetaLegacyBackend, self).run_setup(setup_script=setup_script)
        File "C:\Users\dell\AppData\Local\Temp\pip-build-env-yguajv_e\overlay\Lib\site-packages\setuptools\build_meta.py", line 311, in run_setup
          exec(code, locals())
        File "<string>", line 489, in <module>
        File "<string>", line 469, in setup_package
        File "<string>", line 274, in generate_cython
      RuntimeError: Running cythonize failed!
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

(tf-gpu) C:\Users\dell>pip install -U numpy==1.19.2
Collecting numpy==1.19.2
  Downloading numpy-1.19.2.zip (7.3 MB)
     ---------------------------------------- 7.3/7.3 MB 34.8 kB/s eta 0:00:00
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
  Preparing metadata (pyproject.toml) ... error
  error: subprocess-exited-with-error

  × Preparing metadata (pyproject.toml) did not run successfully.
  │ exit code: 1
  ╰─> [90 lines of output]
      Running from numpy source directory.
      setup.py:470: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
        run_build = parse_setuppy_commands()
      performance hint: _common.pyx:275:19: Exception check after calling 'random_func' will always require the GIL to be acquired. Declare 'random_func' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:299:19: Exception check after calling 'random_func' will always require the GIL to be acquired. Declare 'random_func' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:322:50: Exception check after calling 'random_func' will always require the GIL to be acquired. Declare 'random_func' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:426:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:465:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:509:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:592:36: Exception check after calling 'f0' will always require the GIL to be acquired. Declare 'f0' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:596:36: Exception check after calling 'f1' will always require the GIL to be acquired. Declare 'f1' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:600:36: Exception check after calling 'f2' will always require the GIL to be acquired. Declare 'f2' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:604:36: Exception check after calling 'f3' will always require the GIL to be acquired. Declare 'f3' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:638:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:675:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:712:63: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:754:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:785:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:903:40: Exception check after calling 'f0' will always require the GIL to be acquired. Declare 'f0' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:907:40: Exception check after calling 'fd' will always require the GIL to be acquired. Declare 'fd' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:911:41: Exception check after calling 'fdd' will always require the GIL to be acquired. Declare 'fdd' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:916:40: Exception check after calling 'fi' will always require the GIL to be acquired. Declare 'fi' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:920:41: Exception check after calling 'fdi' will always require the GIL to be acquired. Declare 'fdi' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:924:38: Exception check after calling 'fiii' will always require the GIL to be acquired. Declare 'fiii' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:960:31: Exception check after calling 'f' will always require the GIL to be acquired. Declare 'f' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _common.pyx:1002:32: Exception check after calling 'f1' will always require the GIL to be acquired. Declare 'f1' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
      performance hint: _generator.pyx:707:41: Exception check after calling '_shuffle_int' will always require the GIL to be acquired.
      Possible solutions:
          1. Declare '_shuffle_int' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
          2. Use an 'int' return type on '_shuffle_int' to allow an error code to be returned.
      performance hint: _generator.pyx:736:45: Exception check after calling '_shuffle_int' will always require the GIL to be acquired.
      Possible solutions:
          1. Declare '_shuffle_int' as 'noexcept' if you control the definition and you're sure you don't want the function to raise exceptions.
          2. Use an 'int' return type on '_shuffle_int' to allow an error code to be returned.

      Error compiling Cython file:
      ------------------------------------------------------------
      ...
              for i in range(1, RK_STATE_LEN):
                  self.rng_state.key[i] = val[i]
              self.rng_state.pos = i

              self._bitgen.state = &self.rng_state
              self._bitgen.next_uint64 = &mt19937_uint64
                                         ^
      ------------------------------------------------------------

      _mt19937.pyx:138:35: Cannot assign type 'uint64_t (*)(void *) except? -1 nogil' to 'uint64_t (*)(void *) noexcept nogil'. Exception values are incompatible. Suggest adding 'noexcept' to type 'uint64_t (void *) except? -1 nogil'.
      Processing numpy/random\_bounded_integers.pxd.in
      Processing numpy/random\bit_generator.pyx
      Processing numpy/random\mtrand.pyx
      Processing numpy/random\_bounded_integers.pyx.in
      Processing numpy/random\_common.pyx
      Processing numpy/random\_generator.pyx
      Processing numpy/random\_mt19937.pyx
      Traceback (most recent call last):
        File "C:\Users\dell\AppData\Local\Temp\pip-install-wovy_vlq\numpy_7bca60b545f04327b9b806e784a01c19\tools\cythonize.py", line 235, in <module>
          main()
        File "C:\Users\dell\AppData\Local\Temp\pip-install-wovy_vlq\numpy_7bca60b545f04327b9b806e784a01c19\tools\cythonize.py", line 231, in main
          find_process_files(root_dir)
        File "C:\Users\dell\AppData\Local\Temp\pip-install-wovy_vlq\numpy_7bca60b545f04327b9b806e784a01c19\tools\cythonize.py", line 222, in find_process_files
          process(root_dir, fromfile, tofile, function, hash_db)
        File "C:\Users\dell\AppData\Local\Temp\pip-install-wovy_vlq\numpy_7bca60b545f04327b9b806e784a01c19\tools\cythonize.py", line 188, in process
          processor_function(fromfile, tofile)
        File "C:\Users\dell\AppData\Local\Temp\pip-install-wovy_vlq\numpy_7bca60b545f04327b9b806e784a01c19\tools\cythonize.py", line 77, in process_pyx
          subprocess.check_call(
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\subprocess.py", line 373, in check_call
          raise CalledProcessError(retcode, cmd)
      subprocess.CalledProcessError: Command '['D:\\WorkSpace\\Anaconda_WorkSpace\\envs\\tf-gpu\\python.exe', '-m', 'cython', '-3', '--fast-fail', '-o', '_mt19937.c', '_mt19937.pyx']' returned non-zero exit status 1.
      Cythonizing sources
      Traceback (most recent call last):
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 353, in <module>
          main()
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 335, in main
          json_out['return_val'] = hook(**hook_input['kwargs'])
        File "D:\WorkSpace\Anaconda_WorkSpace\envs\tf-gpu\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 149, in prepare_metadata_for_build_wheel
          return hook(metadata_directory, config_settings)
        File "C:\Users\dell\AppData\Local\Temp\pip-build-env-7cci4yxw\overlay\Lib\site-packages\setuptools\build_meta.py", line 157, in prepare_metadata_for_build_wheel
          self.run_setup()
        File "C:\Users\dell\AppData\Local\Temp\pip-build-env-7cci4yxw\overlay\Lib\site-packages\setuptools\build_meta.py", line 248, in run_setup
          super(_BuildMetaLegacyBackend,
        File "C:\Users\dell\AppData\Local\Temp\pip-build-env-7cci4yxw\overlay\Lib\site-packages\setuptools\build_meta.py", line 142, in run_setup
          exec(compile(code, __file__, 'exec'), locals())
        File "setup.py", line 499, in <module>
          setup_package()
        File "setup.py", line 479, in setup_package
          generate_cython()
        File "setup.py", line 274, in generate_cython
          raise RuntimeError("Running cythonize failed!")
      RuntimeError: Running cythonize failed!
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

(tf-gpu) C:\Users\dell>nvidia-smi
Tue Jan 23 11:21:00 2024
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 546.09                 Driver Version: 546.09       CUDA Version: 12.3     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA GeForce RTX 2080 Ti   WDDM  | 00000000:73:00.0 Off |                  N/A |
| 18%   27C    P8              15W / 250W |      0MiB / 11264MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   1  NVIDIA GeForce RTX 2080 Ti   WDDM  | 00000000:A6:00.0  On |                  N/A |
| 18%   39C    P8              18W / 250W |   1038MiB / 11264MiB |      9%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|    0   N/A  N/A     33204      C   ...der\Program\XMP\Program\APlayer.exe    N/A      |
|    1   N/A  N/A      2508    C+G   C:\Windows\explorer.exe                   N/A      |
|    1   N/A  N/A      7152    C+G   ...3.0_x64__cv1g1gvanyjgm\WhatsApp.exe    N/A      |
|    1   N/A  N/A      7240    C+G   ...1.0_x64__8wekyb3d8bbwe\Video.UI.exe    N/A      |
|    1   N/A  N/A      8168    C+G   ..._x64__kzf8qxf38zg5c\Skype\Skype.exe    N/A      |
|    1   N/A  N/A      8740    C+G   ...1\extracted\runtime\WeChatAppEx.exe    N/A      |
|    1   N/A  N/A     11840    C+G   ..._x64__kzf8qxf38zg5c\Skype\Skype.exe    N/A      |
|    1   N/A  N/A     12860    C+G   ...pIntegrations\Grammarly.Desktop.exe    N/A      |
|    1   N/A  N/A     14032    C+G   ...2txyewy\StartMenuExperienceHost.exe    N/A      |
|    1   N/A  N/A     15468    C+G   ...t.LockApp_cw5n1h2txyewy\LockApp.exe    N/A      |
|    1   N/A  N/A     16956    C+G   ...CBS_cw5n1h2txyewy\TextInputHost.exe    N/A      |
|    1   N/A  N/A     19276    C+G   ...5n1h2txyewy\ShellExperienceHost.exe    N/A      |
|    1   N/A  N/A     20896    C+G   ...86)\Tencent\QQBrowser\QQBrowser.exe    N/A      |
|    1   N/A  N/A     23328    C+G   ...crosoft\Edge\Application\msedge.exe    N/A      |
|    1   N/A  N/A     27128    C+G   ...ogram Files\Unity Hub\Unity Hub.exe    N/A      |
|    1   N/A  N/A     42980    C+G   ....Search_cw5n1h2txyewy\SearchApp.exe    N/A      |
+---------------------------------------------------------------------------------------+
```
