Use ONNX for API model serving

[yanirs]

Key changes:

• Add export_learner_to_onnx command
• Turn fastai, torch, streamlit, and related packages into dev dependencies
• In the API, use the ONNX model for prediction via the thin OnnxWrapper
• Use Poetry for consistent dependencies in the Dockerfile (no more messing around to install the PyTorch CPU version 🎉)
• Add one-off ONNX model evaluation to 03-app.ipynb (more accurate than the fastai Learner 🤔)