lmrescore failure and missing Gr.fst when run the training/run.sh

Hi, dear authors,

I followed the training recipe in the vosk-api/training folder, I did get a trained model, but the performance is not so good.
Also I found the following errors and some mismatch in model structures from the pretrained models. I wondered if there is something I did wrong.
I used the recent official kaldi repo and installed it with cuda on successfully.

1. in the decode stage, steps/lmrescore_const_arpa.sh would fail, and here is the log(maybe there needs to be a specfic version of kaldi?) But there is a WER result at last. I guess just the rescored version failed.

2. I intended to get a model structure similar to "vosk-model-en-us-0.22-lgraph", but there is some difference. this is my exp/chain/tdnn folder.

- First, compared to the pretrained models, I got a HCLG.fst, but not a HCLr.fst and Gr.fst, supposed I need a runtime graph.
- Secondly, I don't find the model.conf file, I tried to collect all the params during training, but maybe not enough. So I just copied the one from "vosk-model-en-us-0.22-lgraph", it worked, but not sure it fits right into my own trained model.
- I map the exp/chain/extractor folder to ivector folder, not sure it works, but the files are similar.

3. From the results I got, I run the python script, test_simple.py, all the output words are upper case also not very precise(since I just run the demo run.sh, the training data couldn't be sufficient, so maybe this is possible, I can attach the audio if necessary, it's a good quality speech with decent pronunciation ), and I got a warning, runtime graphs are not supported, as I mentioned above.

So could you help with this? Am I missing some steps in training or there is some twist I should do after training?
Many thanks~