pyproject.toml

[project]
name = "nested-learning"
version = "0.1.0"
description = "Reproduction of Google's Nested Learning (HOPE) architecture"
license = {text = "Apache-2.0"}
authors = [
  {name = "Nested Learning Team", email = "nested-learning@example.com"}
]
readme = "README.md"
requires-python = ">=3.12"
dependencies = [
  "torch==2.9.0",
  "torchvision==0.24.0",
  "torchaudio==2.9.0",
  "einops>=0.7.0",
  "numpy>=1.26",
  "hydra-core>=1.3.2",
  "omegaconf>=2.3.0",
  "pyyaml>=6.0",
  "tqdm>=4.66",
  "typing-extensions>=4.9",
  "datasets>=2.19,<3.0",
  "sentencepiece>=0.2.0",
  "huggingface-hub>=0.23,<1.0",
  "zstandard>=0.22.0",
  "wandb>=0.18.0",
  "langdetect>=1.0.9",
  "typer>=0.12",
  "matplotlib>=3.8",
]

[project.optional-dependencies]
dev = [
  "pytest>=7.4",
  "pytest-cov>=4.1",
  "ruff>=0.6.8",
  "mypy>=1.11",
  "types-PyYAML",
]

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[tool.pytest.ini_options]
minversion = "7.0"
addopts = "-ra -q"
testpaths = ["tests"]

[tool.ruff]
line-length = 100
target-version = "py312"

[tool.ruff.lint]
select = ["E", "F", "I"]
ignore = []

[tool.mypy]
python_version = 3.12
warn_unused_configs = true
# PyTorch-style codebases inevitably interact with untyped third-party deps and dynamic module calls.
# Keep mypy enabled, but avoid noisy `Any` return warnings for nn.Module forward calls.
ignore_missing_imports = true
warn_return_any = false
strict_optional = true
show_error_codes = true
pretty = true
packages = ["nested_learning"]