quantum-lab
Boilerplate for TorchQuantum Driven Deep Learning Research with PyTorch Lightning and Lightning Fabric
Science Score: 44.0%
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○Scientific vocabulary similarity
Low similarity (11.9%) to scientific vocabulary
Repository
Boilerplate for TorchQuantum Driven Deep Learning Research with PyTorch Lightning and Lightning Fabric
Basic Info
Statistics
- Stars: 1
- Watchers: 0
- Forks: 2
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Quantum Lab
Overview
Quantum Lab is a public template for quantum computing with MIT's TorchQuantum and Lightning AI's PyTorch Lightning.
The recommended way for Quantum Lab users to create new repos is with the use this template button.
Source Module
quantumlab.core should contain code for the Lightning Module and Trainer.
quantumlab.components should contain experiment utilities grouped by purpose for cohesion.
quantumlab.pipeline should contain code for data acquistion and preprocessing, and building a TorchDataset and LightningDataModule.
quantumlab.api should contain code for model serving APIs built with FastAPI.
quantumlab.lab should contain code for the command line interface built with Typer and Rich.
quantumlab.pages should contain code for data apps built with streamlit.
quantumlab.config can assist with project, trainer, and sweep configurations.
Base Requirements and Extras
Quantum Lab installs minimal requirements out of the box, and provides extras to make creating robust virtual environments easier. To view the requirements, in setup.cfg, see install_requires for the base requirements and options.extras_require for the available extras.
The recommended install is as follows:
sh
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[all]"
M Series Macs
There is an issue with the build wheels of one qiskit's dependencies, tweedledum. We can install torchquantum without dependencies using the follow; however, this also means we will need to install dependencies as we begin to work through examples. As such, it is recommended to use this Quantum Lab in a Linux environment.
sh
source .venv/bin/activate
pip install -r requirements.txt
pip install --no-deps git+https://github.com/mit-han-lab/torchquantum.git
Owner
- Login: saeedadeeb103
- Kind: user
- Repositories: 1
- Profile: https://github.com/saeedadeeb103
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: lastName
given-names: firstName
- name: "FirstName LastName"
title: "Project Title"
version: 0.0.1
date-released: 2022-08-06
license: "Apache-2.0"
repository-code: ""
keywords:
- machine learning
- deep learning
- artificial intelligence
GitHub Events
Total
- Watch event: 1
- Fork event: 1
Last Year
- Watch event: 1
- Fork event: 1
Dependencies
- actions/checkout v3 composite
- github/codeql-action/analyze v2 composite
- github/codeql-action/autobuild v2 composite
- github/codeql-action/init v2 composite
- actions/checkout v4 composite
- actions/setup-python v4 composite
- codecov/codecov-action v3 composite
- actions/cache v3 composite
- actions/checkout v4 composite
- actions/setup-python v4 composite
- optuna *
- pytorch-lightning *
- torch *
- torch-tb-profiler *
- wandb *
- rich *
- typer *
- bandit * development
- black * development
- coverage * development
- isort * development
- mypy * development
- pre-commit * development
- pytest * development
- ruff * development
- mkdocs-material *
- mkdocstrings *
- plotly *
- streamlit *
- build *
- setuptools *
- twine *