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File size: 2,002 Bytes
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requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "tsfm-bench"
dynamic = [
"version",
]
dependencies = [
"pandas>=2.2,<2.3",
"gluonts>=0.16,<0.17",
"numpy>=1.26,<2",
"python-dotenv>=1.1,<2",
"scipy>=1.11,<1.12",
"pyyaml>=6,<7",
"httpx>=0.27,<0.29",
"requests>=2.32,<3",
"huggingface_hub>=0.23,<0.35.3",
"statsmodels>=0.14,<0.15",
]
requires-python = ">=3.10,<3.13"
authors = [
{name = "Taha Aksu", email = "iaksu@salesforce.com"},
{name = "Gerald Woo", email = "gwoo@salesforce.com"},
{name = "Chenghao Liu", email = "chenghao.liu@salesforce.com"},
{name = "Juncheng Liu", email = "juncheng.liu@salesforce.com"},
{name = "Xu Liu", email = "xu.liu@salesforce.com"},
{name = "Caiming Xiong"},
{name = "Silvio Savarese"},
{name = "Doyen Sahoo"},
]
maintainers = [
{name = "Thinkcat-Lab"},
]
description = "LiveHouse-TS: a live benchmark for time series foundation models"
#readme = "README.md"
#license = {file = "LICENSE.txt"}
keywords = ["Time Series Forecasting", "Transformer", "Deep Learning", "PyTorch"]
classifiers = [
"Development Status :: 3 - Alpha",
"Programming Language :: Python",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
]
[project.optional-dependencies]
leaderboard = ["gradio==4.44.0", "pydantic>=2.7,<2.11", "plotly>=5,<6", "matplotlib>=3.9,<3.10"]
dev = ["pytest>=8,<9", "fastapi==0.112.4", "uvicorn==0.30.6"]
gift = ["datasets~=2.17.1", "einops==0.7.*", "hydra-core==1.3", "orjson", "matplotlib~=3.9.2", "tsfeatures", "ray"]
tabpfn-ts = [
"tabpfn-time-series>=1.1.0; python_version >= '3.10'",
]
baseline = [
"torch>=2.1",
"statsforecast",
"tensorboard",
"torch>=2.1",
"lightning>=2.0",
]
[tool.hatch.version]
path = "src/gift_eval/__about__.py"
[tool.hatch.build]
packages = ["src/gift_eval", "src/tsfm_bench"]
[tool.isort]
profile = "black"
[tool.black]
line-length = 88
target-version = ['py310']
[tool.pytest.ini_options]
pythonpath = [
".", "src",
]
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