This workshop content covers:
- a brief introduction to deep learning and TensorFlow 2.0
- using
tf.data
and TensorFlow Datasets - XLA compiler and Automatic Mixed Precision (AMP)
- speeding up CNN (ResNet-50) with XLA and AMP
- speeding up Transformer (BERT) with XLA and AMP
For a quick guide to using Automatic Mixed Precision, check out this TLDR.
Slides are in this Google Drive folder.
Notebooks
Notebook | Link | Solution |
---|---|---|
TensorFlow Dataset & tf.data | ||
Pet Classification with TF 2.0 | ||
Transformers with TF 2.0 |
For those running the notebooks on the workshop JupyterHub or on your own hardware, you can clone this repository.
git clone https://github.com/NVAITC/pycon-sg19-tensorflow-tutorial
In-person @ PyCon SG 2019
- Attend the workshop 10am to 1pm on Saturday, October 12 at Republic Polytechnic.
- Get your tickets here.