D3R
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Feat/add docker support
Summary
This PR adds Docker support to provide a standardized and highly reproducible execution environment for the D3R project. This is crucial for ensuring that the specific environmental dependencies (PyTorch 1.11.0 / CUDA 11.3 / Python 3.9) can be consistently and easily deployed across different machines.
Key Changes
- New
Dockerfile:- Uses
pytorch/pytorch:1.11.0-cuda11.3-cudnn8-runtimeas the base image. - Crucial Optimization: Core dependencies (like
numpy,pandas,scikit-learn, etc.) are installed directly viapip installwithin the Dockerfile to prevent common installation conflicts associated with locking versions inrequirements.txtfor this specific Python 3.9 environment.
- Uses
- Updated
README.md:- Introduces a concise "If you prefer Docker..." block, providing clean instructions for building and running experiments, including the necessary volume mount (
-v .:/app/data) for easy dataset access.
- Introduces a concise "If you prefer Docker..." block, providing clean instructions for building and running experiments, including the necessary volume mount (