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System information

• TensorFlow version: 1.13.1
• Doc Link: https://www.tensorflow.org/api_docs/python/tf/cus

(e.g. for links and images), because some of these examples are now being rendered in the docs.

Added by @fchollet in requests for contributions.

The array API specification stipulates four numeric constants:

• e
• inf
• nan
• pi

PyTorch currently supports none.

cc @mruberry @rgommers @pmeier

We should be using pkg_resources (or importlib.resources if our min Python version is 3.7) instead of uses of __file__.

$ get grep '__file__' sklearn/
sklearn/__check_build/__init__.py:    local_dir = os.path.split(__file__)[0]
sklearn/datasets/_base.py:    module_path = dirname(__file__)
sklearn/datasets/_base.py:    module_path = dirname(__file__)
sklearn/datasets/_base.py:    

I received this error message:

  MethodError: convert(::Type{Union{}}, ::Vector{Float32}) is ambiguous. Candidates:
    convert(::Type{T}, a::AbstractArray) where T<:Array in Base at array.jl:532
    convert(T::Type{var"#s79"} where var"#s79"<:BitArray, a::AbstractArray) in Base at bitarray.jl:577
    convert(T::Type{var"#s832"} where var"#s832"<:SparseArrays.SparseVector, m::AbstractVect

Currently many more Python projects like dask and optuna are using Python type hints. With the Python package of xgboost gaining more and more features, we should also adopt mypy as a safe guard against some type errors and for better code documentation.