TFlite Model Maker installation successfull - but error on import
I could also reproduce the issue when installing model maker from pip (version 0.4.2)

```
conda install tensorflow=2.8.2=gpu_py38h75b8afa_0
pip install tflite-model-maker
pip install numpy==1.23.5
python
>>> from tflite_model_maker.config import QuantizationConfig
```

Then the error like above: 

```
tensorflow.python.framework.errors_impl.NotFoundError: /home/alex/anaconda3/envs/tf_gpu_env_mm_pip/lib/python3.8/site-packages/scann/scann_ops/cc/_scann_ops.so: undefined symbol: _ZN4absl12lts_2021032420raw_logging_internal21internal_log_functionE
``` @alexw92, This issue is unlikely to be resolved soon, Could you please use [mediapipe model maker](https://developers.google.com/mediapipe/solutions/model_maker) instead for now. Here is also a [gist](https://colab.sandbox.google.com/gist/pkgoogle/93fb7581fab1ea14728c61adf584ca13/media_pipe_example.ipynb) that runs through some image classification examples with mediapipe model maker, including quantization: gist. If you can't accomplish your goals with mediapipe-model-maker please let us know and we'll see if there is a way to accomplish your goals.

https://github.com/tensorflow/tensorflow/issues/60431

Thank you! @tilakrayal Hello and thanks for your response. Yes it looks interesting and I thing it will work! But how do I install it? When I try to install mediapipe model maker via pip, pip ignores my already installed conda tensorflow 2.10 environment and loads tf 2.15 from pip which wont work for me since it uses AVX. I think even the old model maker will work if I can find out the reason for the error above. @alexw92 Could you consider creating a new, clean conda environment specifically for the mediapipe-model-maker to avoid conflicts with other packages or TensorFlow versions.
Thank you! @sushreebarsa Sure thats what I have been doing for the last couple of days. I always started within a new conda environment and tried so many different configurations and package versions. I was not able to create one single environment where mediapipe-model-maker was using the already installed (installed within conda using conda install of course not globally) tensorflow version. So I wonder if this is even possible. Btw for this I created another issue since this one is referring to the traditional model maker while the other [issue ](https://github.com/google/mediapipe/issues/5033#) is in the mediapipe repo  @alexw92 Could you double-check the import statement for accuracy and ensure you're using the correct path to the model maker module?
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. @sushreebarsa I checked the import statement and yes it is correct definetly! The import is actually from the samples page of tf lite model maker. 
By the way, is tf lite model maker about to be substituted completly by mediapipe model maker? So is there a recommendation by Google to always use mediapipe model maker instead of the one in this repo? Hi @pkgoogle, 

Please look into the issue

Thank You Hi @alexw92, you have a couple of options:

1. Just use [mediapipe model maker](https://developers.google.com/mediapipe/solutions/model_maker) in colab (You can use a GPU/TPU here as well though there are potential limitations) https://research.google.com/colaboratory/faq.html
2. Attempt to fix your current setup, can you try `pip install scann`?
3. Build Tensorflow from source w/o AVX support and with Cuda(Nvidia GPUs)/RocM(AMD GPUs) support https://www.tensorflow.org/install/source (For WSL you would follow linux instructions), then try to simultaneously install all your required packages with the built package so that they have the best chance to play nicely together
4. Use a lower level API and skip tflite-model-maker/mediapipe-model-maker and use [keras](https://keras.io/)/[TF](https://www.tensorflow.org/tutorials) directly

I think b/c you don't have AVX support and we essentially aren't supporting older versions, these are your best choices, let me know if any of them work and we can try to pursue those choices further. @pkgoogle  
1) Yes I am aware of this thanks.
2) I did and this did not work unfortunately. Also uninstalling and reinstalling scann did not work
3) This is what I am afraid of. I have no experience in building from source.
4) That would mean throwing thousands lines of code away I already wrote for working with model-maker

What I did in the end was borrowing another system which an AVX-capable CPU. It is really sad that newer TF versions are build to require AVX even though the majority of users will use their GPU anyway. I will update my system with a new CPU then since it seems to be the quickest solution. 

By the way could you please tell me:
**Maintenance Status:** Is the Model Maker located in the examples directory of the TensorFlow repository still actively maintained? Or has it been superseded by the MediaPipe Model Maker?

**Official Recommendation:** For developing models, especially with a focus on mobile and edge devices, does Google currently recommend transitioning to the MediaPipe Model Maker? Hi @alexw92,

Be careful with motherboard compatibility if you go that route.

> Maintenance Status: Is the Model Maker located in the examples directory of the TensorFlow repository still actively maintained? Or has it been superseded by the MediaPipe Model Maker?

Model Maker is currently still active but is running into the problems you have seen, so that's why we are diverting users to MediaPipe Model Maker. Effectively and practically if you want anything done right now, yes ... I can't say if that will continue to be the case in the future.

> Official Recommendation: For developing models, especially with a focus on mobile and edge devices, does Google currently recommend transitioning to the MediaPipe Model Maker?

Yes or TFLite directly, as always, the lower you go in the API the more customizability you have at the cost of developer experience.

> 3. This is what I am afraid of. I have no experience in building from source.

Of course you know the best use of your own time, but the only way to get experience is to try 😄. Your experience here will be smoother on linux/WSL. Building from source is generally the most reliable way to support unique configurations/combinations -- or see why that configuration/combination is not supported. 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/62658">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/62658">No</a>

### Issue type

Bug

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

No

### Source

binary

### TensorFlow version

2.8.2

### Custom code

No

### OS platform and distribution

WSL Ubuntu 20.04 on Windows 10

### Mobile device

_No response_

### Python version

3.8

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

I thought I have successfully installed TFLite model maker but I can an error when trying to test code which happens on some imports. It seems to be scann related which is installed at version 1.2.6 by pip which should be compatible.
One important thing might be that I installed tensorflow 2.8.2 using anaconda because the pip packages are built requiring AVX which my CPU does not have. I verified that my GPU is used correctly within the anaconda environment with this installed package though.

The following error happens on imports e.g. ```from tflite_model_maker.config import QuantizationConfig```:

```
python
Python 3.8.18 (default, Sep 11 2023, 13:20:55)
[GCC 11.2.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from tflite_model_maker import object_detector
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/alex/examples/tensorflow_examples/lite/model_maker/pip_package/src/tflite_model_maker/__init__.py", line 51, in <module>
    from tflite_model_maker import searcher
  File "/home/alex/examples/tensorflow_examples/lite/model_maker/pip_package/src/tflite_model_maker/searcher/__init__.py", line 25, in <module>
    from tensorflow_examples.lite.model_maker.core.task.searcher import ExportFormat
  File "/home/alex/examples/tensorflow_examples/lite/model_maker/pip_package/src/tensorflow_examples/lite/model_maker/core/task/searcher.py", line 30, in <module>
    from tensorflow_examples.lite.model_maker.core.utils import ondevice_scann_builder
  File "/home/alex/examples/tensorflow_examples/lite/model_maker/pip_package/src/tensorflow_examples/lite/model_maker/core/utils/ondevice_scann_builder.py", line 17, in <module>
    from scann.proto import scann_pb2
  File "/home/alex/anaconda3/envs/tf_gpu_env/lib/python3.8/site-packages/scann/__init__.py", line 2, in <module>
    from scann.scann_ops.py import scann_ops
  File "/home/alex/anaconda3/envs/tf_gpu_env/lib/python3.8/site-packages/scann/scann_ops/py/scann_ops.py", line 23, in <module>
    _scann_ops_so = tf.load_op_library(
  File "/home/alex/anaconda3/envs/tf_gpu_env/lib/python3.8/site-packages/tensorflow/python/framework/load_library.py", line 54, in load_op_library
    lib_handle = py_tf.TF_LoadLibrary(library_filename)
tensorflow.python.framework.errors_impl.NotFoundError: /home/alex/anaconda3/envs/tf_gpu_env/lib/python3.8/site-packages/scann/scann_ops/cc/_scann_ops.so: undefined symbol: _ZN4absl12lts_2021032420raw_logging_internal21internal_log_functionE
```

Is it related that I use tensorflow from conda and not from pip?




### Standalone code to reproduce the issue

```shell
This is what i did in WSL

~$ conda install tensorflow=2.8.2=gpu_py38h75b8afa_0
~$ python
>>> import tensorflow as tf
>>> tf.config.list_physical_devices('GPU')
2023-12-18 01:18:17.785271: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:922] could not open file to read NUMA node: /sys/bus/pci/devices/0000:02:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-12-18 01:18:17.799686: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:922] could not open file to read NUMA node: /sys/bus/pci/devices/0000:02:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-12-18 01:18:17.800511: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:922] could not open file to read NUMA node: /sys/bus/pci/devices/0000:02:00.0/numa_node
Your kernel may have been built without NUMA support.
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]

~$ pip install -q pycocotools
~$ pip install -q opencv-python-headless==4.1.2.30
~$ sudo apt -y install libportaudio2

~/examples/tensorflow_examples/lite/model_maker/pip_package$ pip install -e .
~/examples/tensorflow_examples/lite/model_maker/pip_package$ python
>>> from tflite_model_maker.config import QuantizationConfig
```
```


### Relevant log output

_No response_