Hi everyone,
I am currently working on deploying and fine-tuning a TFLite model. My goal is to be able to run inference (which currently already works) as well as continue training using only TFLite. To achieve this goal, I have followed this tutorial.
I have build TFlite Wheel natively on my edge device with cmake, following instructions here : টেনসরফ্লো লাইট পাইথন হুইল প্যাকেজ তৈরি করুন | TensorFlow Lite
However, when running my script, I encounter the following problem.
Select TensorFlow op(s), included in the given model, is(are) not supported by this interpreter. Make sure you apply/link the Flex delegate before inference. For the Android, it can be resolved by adding “org.tensorflow:tensorflow-lite-select-tf-ops” dependency. See instructions: https://www.tensorflow.org/lite/guide/ops_selectNode number 32 (FlexRestore) failed to prepare.
By doing some desktop research, I found out that Flex Delegate Operations need to be installed to continue the training with TFLite only. Is installing the Flex Delegate Operations when building TFLite with CMake on Python possible?
I am asking this question because I found very little to no guidance online on how to enable Flex Delegate Operations in Python. The only guide I found is this one but it only mentions an experimental method based on Bazel and I would highly prefer to use CMake. Is this possible? (I am using Python 3.10.10 and I cannot install the full TF package).
Thank you very much in advance.