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pyproject.toml
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pyproject.toml
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[tool.poetry]
name = "gflownet"
version = "0.1.0"
description = "GFlowNets, generative flow networks for probabilistic modelling"
authors = ["Alex <[email protected]>"]
readme = "README.md"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
[tool.poetry.dependencies]
# Base dependencies.
botorch = ">=0.10.0"
hydra-core = ">=1.3.2"
matplotlib = "*"
numpy = "*"
pandas = "*"
plotly = ">=5.17.0"
scikit-learn = ">=1.2.2"
scipy = ">=1.11.2"
six = ">=1.16.0"
torch = "==2.0.1"
torchtyping = ">=0.1.4"
tqdm = "*"
wandb = ">=0.15.11"
# Dev dependencies.
black = { version = ">=23.9.1", optional = true }
flake8 = { version = ">=6.1.0", optional = true }
isort = { version = ">=5.12.0", optional = true }
pylint = { version = ">=2.17.6", optional = true }
ipdb = { version = ">=0.13.13", optional = true }
jupyter = { version = ">=1.0.0", optional = true }
pytest = { version = ">=7.4.2", optional = true }
pytest-repeat = { version = ">=0.9.1", optional = true }
# Materials / crystal environments.
pymatgen = {version = ">=2023.12.18", optional = true }
pyxtal = {version = ">=0.6.1", optional = true }
# To potentially update! Also, this really should be named activelearningproxy.
dave = { git = "https://github.com/sh-divya/ActiveLearningMaterials.git", rev = "0.3.4", optional = true }
pyshtools = {version = "==4.10.3", optional = true }
# Molecules.
# TODO: Remove Handled (for now) via a specialized script.
# pyg_lib = {version = "0.3.1+pt20cu118", optional = true }
# torch-scatter = { version = "2.1.2+pt20cu118", optional = true }
# torch-sparse = { version = "0.6.18+pt20cu118", optional = true }
# torch-cluster = {version = "1.6.3+pt20cu118", optional = true }
# torch-spline-conv = {version = "1.2.2+pt20cu118", optional = true }
torch-geometric = { version = ">=2.3.1", optional = true }
torchani = { version = "2.2.4", optional = true }
rdkit = { version = "2023.3.1", optional = true }
[tool.poetry.extras]
dev = [
"black",
"flake8",
"isort",
"pylint",
"ipdb",
"jupyter",
"pytest",
"pytest-repeat",
]
materials = ["pymatgen", "pyxtal", "dave", "pyshtools"]
molecules = [
"pyg_lib",
"torch-geometric",
"torch-scatter",
"torch-sparse",
"torch-cluster",
"torch-spline-conv",
"torchani",
"rdkit",
]
all = [
"black",
"flake8",
"isort",
"pylint",
"ipdb",
"jupyter",
"pytest",
"pytest-repeat",
"pymatgen",
"pyxtal",
"dave",
"pyshtools",
"pyg_lib",
"torch-scatter",
"torch-sparse",
"torch-cluster",
"torch-spline-conv",
"torchani",
"rdkit",
]