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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.

It should be added to the .rst so that they appear on the website.
Doc is already inline here https://github.com/pytorch/pytorch/blob/df88cc3f7f5c13221a93d7d3d38e681a3d5a6b6a/torch/nn/modules/module.py#L89-L115

cc @jlin27 @mruberry

Most functions in scipy.linalg functions (e.g. svd, qr, eig, eigh, pinv, pinv2 ...) have a default kwarg check_finite=True that we typically leave to the default value in scikit-learn.

As we already validate the input data for most estimators in scikit-learn, this check is redundant and can cause significant overhead, especially at predict / transform time. We should probably a

One of the main use cases of lpad and rpad is, at least for me personally, to align things in the terminal. However, lpad and rpad are defined (and documented) to work in terms of code units (i.e. they call length on the input string) which means that when length and textwidth disagree, you get unaligned output:

julia> s1 = "⟨k|H₁|k̃⟩"
"⟨k|H₁|k̃⟩"
julia> s2 = "⟨k|H₁|k⟩"
"⟨

Currently, the C++ compiler generates lots of warnings: https://xgboost-ci.net/blue/organizations/jenkins/xgboost/detail/master/516/pipeline/61. It would be great to reduce the number of warnings.

Note to new contributors: Post a comment here if you'd like to work on this issue. Feel free to ping me for help.