This notebook provides scripts for you to run Jasper with TRT for inference step by step. You can run inference using either LibriSpeech dataset or your own audio input in .wav format, to generate the corresponding text file for the audio file.
This repository contains a Dockerfile which extends the PyTorch 19.09-py3 NGC container and encapsulates some dependencies. Aside from these dependencies, ensure you have the following components:
Running the following scripts will build and launch the container containing all required dependencies for both TensorRT as well as native PyTorch. This is necessary for using inference with TensorRT and can also be used for data download, processing and training of the model.
The Jasper PyTorch container will be launched in the Jupyter notebook. Within the container, the contents of the root repository will be copied to the /workspace/jasper directory.
The /datasets, /checkpoints, /results directories are mounted as volumes and mapped to the corresponding directories "data" "checkpoint" "result" on the host.
#### 5. Copy the notebook to the root
Copy the notebook to the root directory of Jasper:
Use the token listed in the output from running the jupyter command to log in, for example: `http://[host machine]:8888/?token=aae96ae9387cd28151868fee318c3b3581a2d794f3b25c6b`