Memory allocation when transcribing
Hi

I'm building a communication API for transcription with NeMo and I ran into a critical infinite memory allocation problem.
When using a lib that monitors memory allocation, I noticed that the "transcribe" method used on top of a restored model is allocating memory every time when transcribing a new file.
My API basically works like this:
When starting, I load the .nemo model creating the asr_model, then open a listener and keep receiving hundreds of files on the network, carrying out their individual transcription on top of that same nemo_asr object.
At this point the problem comes up, because every time I call the transcribe method it keeps allocating more and more memory... I left it running for a night and it allocated 50GB of ram (considering a small stream of audios to transcribe)
Is there an alternative so I can work around this problem? I don't think it's perfect to have to create a new nemo_asr object every time I transcribe, so I keep it in this format.
Here are two examples below:
![Ev1](https://user-images.githubusercontent.com/49459897/131869414-b711961f-0640-4f73-8078-1e15d6832787.PNG)
![Ev2](https://user-images.githubusercontent.com/49459897/131869432-3e259a63-a8c2-4165-bdb2-88ada3ffc860.PNG)

SO: Ubuntu 18.04
Nemo: 1.2.0