Bug: lm_optimize fails due to check failing.

[BjornTheProgrammer]

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Describe the bug When attempting to run the optimizer python script to determine the best alpha and beta for a customer scorer, it errors with the following output on an M1 Macbook 2020 running macOS Monterey 12.5.1.

python3 lm_optimizer.py
2022-09-30 12:37:43.198725: F tensorflow/core/lib/monitoring/sampler.cc:42] Check failed: bucket_limits_[i] > bucket_limits_[i - 1] (0 vs. 10)
qemu: uncaught target signal 6 (Aborted) - core dumped
Aborted

To Reproduce Steps to reproduce the behavior:

1. Run docker pull ghcr.io/coqui-ai/stt-train:v0.10.0-alpha.4
2. Run docker run -it --name stt-test --entrypoint /bin/bash ghcr.io/coqui-ai/stt-train:v0.10.0-alpha.4
3. Make file at /code/data/text.txt with following data

   up
   down
   left
   right
   velocity
   distance
   forward
   backward
   faster
   slower
   stop
   start
   take off
   land
   launch

4. Run python3 generate_lm.py --input_txt /code/data/text.txt --output_dir /code/data/ --top_k 500000 --kenlm_bins /code/kenlm/build/bin/ --arpa_order 5 --max_arpa_memory "85%" --arpa_prune "0|0|1" --binary_a_bits 255 --binary_q_bits 8 --binary_type trie --discount_fallback
5. Run python3 lm_optimizer.py
6. See error

Expected behavior To receive an optimized alpha and beta

Environment (please complete the following information):

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): macOS Monterey 12.5.1

• TensorFlow installed from (our builds, or upstream TensorFlow): Whatever build that is within the docker

• TensorFlow version (use command below): Whatever that is within the docker

• Python version: Whatever that is within the docker

• Bazel version (if compiling from source): Whatever that is within the docker

• GCC/Compiler version (if compiling from source): Whatever that is within the docker

• CUDA/cuDNN version: Whatever that is within the docker

• GPU model and memory: No GPU being utilized

• Exact command to reproduce:

Additional context Add any other context about the problem here.

[wasertech]

Why are your using v0.10.0-alpha.4 ? Try with the latest 1.4.0 if it’s still doesn’t work, it’s because your are using an M1 Mac. Which as far as I know is not supported yet for inference. I’m not even sure training will ever be supported on Apple Silicone laptops…

[BjornTheProgrammer]

Thank you, I was using an M1 MacBook, and I apologize for wasting your time, I attempted many fixes not stated here to solve the import error and apparently fixed them, but couldn't get the final TensorFlow issue to work. So I have given up on utilizing the lm_optomizer on my Mac. Thanks again for your help.