content: [build-system]
  requires = ["setuptools>=66"]
  
  [project]
  name = "ProbTS"
  version = "0.1.0"
  description = "Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons"
  authors = [
      {name = "Jiawen Zhang"},
      {name = "Xumeng Wen"},
      {name = "Zhenwei Zhang"},
      {name = "Shun Zhen"},
  ]
  readme = "README.md"
  requires-python = ">=3.10"
  license = {text = "MIT"}
  
  dependencies = [
      "numpy",
      "pandas==2.0.3",
      "einops",
      "matplotlib",
      "tqdm",
      "PyYAML>=6.0",
      "lightning @ https://github.com/Lightning-AI/lightning/archive/refs/heads/master.zip",
      "gluonts~=0.15.1",
      "typeshed-client==2.3.0",
      "docstring-parser==0.15",
      "orjson==3.9.0",
      "einops>=0.6.1",
      "pydantic==1.10.8",
      "transformers==4.50.0",
      "linear-attention-transformer==0.19.1",
      "tensorboardx==2.6.2",
      "pyarrow==11.0.0",
      "protobuf>=3.19",
      "jsonargparse[signatures]==4.27.7",
      "opt_einsum",
      "psutil",
      "reformer-pytorch",
      "gdown",
      "kagglehub",
      "python-dotenv>=1.0.0",
      "utilsforecast",
      "jax",
      "scikit-learn",
  ]
  
  [project.optional-dependencies]
  tsfm = [
      "timm",
      "accelerate",
      "tokenizers",
      "datasets",
      "jaxtyping",
      "hydra-core==1.3",
      "orjson",
      "tensorboard",
      "multiprocess",
      "huggingface_hub>=0.23.0",
      "safetensors",
      "jax[cpu]",
      "paxml>=1.4.0", # for timesfm
      "praxis>=1.4.0",
      "einshape>=1.0.0",
      "numpy>=1.26.4",
      "pandas==2.0.3",
      "pykeops",
  ]
  
  [tool.setuptools]
  py-modules = []