Problem converting from saved model to tflite model
Hi @NotPjoker05,

Could you please fill the [template](https://github.com/tensorflow/tensorflow/issues/new/choose) to resolve the issue.
As well try the code with tensorflow 2.15 version if not tried.

Thank You I'm already using tensorflow 2.15.
### 1. System information

- Windows 10:
- Tensorflow installed with pycharm gui:
- TensorFlow 2.15 :

### 2. Code
Here are my 3 files, Training for training my model, utils provides a list of methods used in training and test is the class where I use my model (predictions work in tensorflow but the method for converting from saved model  to tflite doesn't work)

[Training.txt](https://github.com/tensorflow/tensorflow/files/13665686/Training.txt)
[utils.txt](https://github.com/tensorflow/tensorflow/files/13665687/utils.txt)
[Test.txt](https://github.com/tensorflow/tensorflow/files/13665685/Test.txt)



### 3. Failure after conversion
When I try to convert my model with the code in Test class I receive this error:
loc(fused["ReadVariableOp:", "sequential_1/conv2d_1/ReadVariableOp@__inference_serving_default_285"]): error: missing attribute 'value'
LLVM ERROR: Failed to infer result type(s).

Please help me, I've been stuck on this error for weeks... @NotPjoker05 , 
Please provide the input data to reproduce the error.
Thank You Sure, this is my dataset:
https://mega.nz/file/UrVUEDIK#mHkxTofcMjTWiBMzbALDDbnh1CJkZgpsKTezd5zgXTc 

Thank you very much!
 Hi @NotPjoker05 ,

Sorry for the delay, I have executed the code in colab 2.15. It's working as expected. The  saved model inference and tflite inference(both ```model.tflite``` and ```converted_model.tflite```) are the same as expected. Please find the [gist.](https://colab.research.google.com/gist/LakshmiKalaKadali/879c701a8a66ea624071ecc0c2ddb923/-62610.ipynb)

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/62610">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/62610">No</a>
 Same issue. Colab crash without any error.. Just in case it helps others like me struggling with this issue. I realized I was using TensorFlow 2.16.1 , from docker image tensorflow:latest-gpu and that was the source of the problem.
I switched to docker image tensorflow:2.15.0-gpu and the problem went away, all working fine now. @adamantivm Thanks for helping with my project, good idea! Solved this problem. Same issue.
Hi, I'm trying to convert my model (saved in 'saved model' format) to a tflite model but I get an error, this is my code: 

`converter = tf.lite.TFLiteConverter.from_saved_model('saved_model')
tflite_model = converter.convert()

with open('model.tflite', 'wb') as f:
  f.write(tflite_model)`

The error is this:
_**loc(fused["ReadVariableOp:", "sequential_1/conv2d_1/ReadVariableOp@__inference_serving_default_285"]): error: missing attribute 'value'
LLVM ERROR: Failed to infer result type(s).**_

I read the tensorflow page related to the topic and it explains that a refactoring of my model is probably necessary, so I tried to follow the indication but the error I get is the same (my other code is this:)

`
import tensorflow as tf

converter = tf.lite.TFLiteConverter.from_saved_model('saved_model')
converter.target_spec.supported_ops = [
  tf.lite.OpsSet.TFLITE_BUILTINS, # enable TensorFlow Lite ops.
  tf.lite.OpsSet.SELECT_TF_OPS # enable TensorFlow ops.
]
tflite_model = converter.convert()
open("converted_model.tflite", "wb").write(tflite_model)
`
I hope someone is able to help me, thanks in advance