mirror of
https://github.com/finegrain-ai/refiners.git
synced 2024-11-14 00:58:13 +00:00
145 lines
3.5 KiB
TOML
145 lines
3.5 KiB
TOML
[project]
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name = "refiners"
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version = "0.3.1"
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description = "The simplest way to train and run adapters on top of foundation models"
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authors = [{ name = "The Finegrain Team", email = "bonjour@lagon.tech" }]
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license = "MIT"
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dependencies = [
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"torch>=2.1.1",
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"safetensors>=0.4.0",
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"pillow>=10.1.0",
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"jaxtyping>=0.2.23",
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"packaging>=23.2",
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]
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readme = "README.md"
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requires-python = ">= 3.10"
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classifiers = [
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"Typing :: Typed",
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"Intended Audience :: Developers",
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"Intended Audience :: Science/Research",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Topic :: Software Development :: Libraries :: Python Modules",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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"License :: OSI Approved :: MIT License",
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]
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[project.optional-dependencies]
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training = [
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"bitsandbytes>=0.41.2.post2",
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"pydantic>=2.5.2",
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"prodigyopt>=1.0",
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"torchvision>=0.16.1",
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"loguru>=0.7.2",
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"wandb>=0.16.0",
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"datasets>=2.15.0",
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"tomli>=2.0.1",
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]
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test = [
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"diffusers>=0.26.1",
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"transformers>=4.35.2",
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"piq>=0.8.0",
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"invisible-watermark>=0.2.0",
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"torchvision>=0.16.1",
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# An unofficial Python package for Meta AI's Segment Anything Model:
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# https://github.com/opengeos/segment-anything
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"segment-anything-py>=1.0",
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]
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conversion = [
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"diffusers>=0.26.1",
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"transformers>=4.35.2",
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"segment-anything-py>=1.0",
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"requests>=2.26.0",
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"tqdm>=4.62.3",
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]
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doc = [
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# required by mkdocs to format the signatures
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"black>=24.1.1",
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"mkdocs-material>=9.5.6",
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"mkdocstrings[python]>=0.24.0",
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"mkdocs-literate-nav>=0.6.1",
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]
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.rye]
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managed = true
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dev-dependencies = [
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"pyright==1.1.349",
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"ruff>=0.2.0",
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"docformatter>=1.7.5",
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"pytest>=8.0.0",
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"coverage>=7.4.1",
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"typos>=1.18.2",
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]
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[tool.hatch.metadata]
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allow-direct-references = true
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[tool.rye.scripts]
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lint = { chain = ["ruff format .", "ruff --fix ."] }
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serve-docs = "mkdocs serve"
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test-cov = "coverage run -m pytest"
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# Work around for "Couldn't parse" errors due to e.g. opencv-python:
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# https://github.com/nedbat/coveragepy/issues/1653
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build-html-cov = { cmd = "coverage html", env = { PYTHONWARNINGS = "ignore:Couldn't parse::coverage.report_core" } }
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serve-cov-report = { chain = [
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"build-html-cov",
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"python -m http.server 8080 -b 127.0.0.1 -d htmlcov",
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] }
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[tool.black]
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line-length = 120
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[tool.ruff]
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src = ["src"] # see https://docs.astral.sh/ruff/settings/#src
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line-length = 120
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[tool.ruff.lint]
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select = [
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"I", # isort
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]
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ignore = [
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"F722", # forward-annotation-syntax-error, because of Jaxtyping
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"E731", # do-not-assign-lambda
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]
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[tool.ruff.lint.isort]
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# Allow this kind of import on a single line:
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#
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# from torch import device as Device, dtype as DType
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#
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combine-as-imports = true
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[tool.docformatter]
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black = true
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[tool.pyright]
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include = ["src/refiners", "tests", "scripts"]
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strict = ["*"]
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exclude = ["**/__pycache__", "tests/weights"]
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reportMissingTypeStubs = "warning"
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[tool.coverage.run]
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branch = true
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source = ["src/refiners"]
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# Also apply to HTML output, where appropriate
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[tool.coverage.report]
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ignore_errors = true # see `build-html-cov` for details
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exclude_also = [
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"def __repr__",
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"raise NotImplementedError",
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"if TYPE_CHECKING:",
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"class .*\\bProtocol\\):",
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"@(abc\\.)?abstractmethod",
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]
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[tool.typos.default]
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extend-words = { adaptee = "adaptee" }
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extend-ignore-identifiers-re = ["NDArray*"]
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