This repository contains the code that acheived 39th place in Google AI4Code ā Understand Code in Python Notebooks.
- numpy
- omegaconf
- pandas
- pytorch_lightning
- scikit_learn
- torch
- tqdm
- fasttext
- sentencepiece
- transformers
- wandb
Instead of installing the above modules independently, you can simply do at once by using:
$ pip install -f requirements.txt -f https://download.pytorch.org/whl/torch_stable.htmlThis repository supports NVIDIA Apex. It will automatically detect the apex module and if it is found then some training procedures will be replaced with the highly-optimized and fused operations in the apex module. Run the below codes in the terminal to install apex and enable performance boosting:
$ git clone https://github.com/NVIDIA/apex
$ sed -i "s/or (bare_metal_minor != torch_binary_minor)//g" apex/setup.py
$ pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" apex/
$ rm -rf apexInstead, we recommend to use docker and PyTorch NGC Container where apex, optimized cuda driver and faster pytorch kernel are installed:
$ docker run --gpus all -it nvcr.io/nvidia/pytorch:22.07-py3