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System information

• Have I written custom code (as opposed to using a stock
  example script provided in TensorFlow): Yes

currently, some of the programs use static type checking like this program but some of the programs did not use static typing.

it's a good practice to use static typing as it makes code more clear and readable, should we make it a standard for this repository.we can use mypy for

(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.

Describe the issue linked to the documentation

Follows from #17387

Suggest a potential alternative/fix

Stop referencing preprocessing functions e.g. :

maxabs_scale
minmax_scale
normalize
quantile_transform
robust_scale
scale
power_transform

in the UG, and only add them e.g. in the "See Also" sections, or even just in the API ref.

In particular right now the first entr

🐛 Bug

Follow up on #43476.
Scanning CUDA KernelUtils.GET_BLOCKS might be called with overflowed 32bit integers. should convert to int64 to hold num_kernels

Additional context

See examples such as:
https://github.com/pytorch/pytorch/blob/c010ef7f0c6d837809a7e973048afac76373e3de/aten/src/ATen/native/cuda/vol2col.cuh#L107

https://github.com/pytorch/pytorch/blob/c010ef7f0c6d83780

It looks like Travis support specifying such a Python version as 3.9-dev.

While I’m not sure we should officially support Python 3.9 it until its release, running tests on it will allow us to catch any issue early.

This issue tracks Superset's migration from JavaScript to TypeScript (as started in SIP-36). If you'd like to help with the migration, feel free to take an unchecked directory and convert the files within the immediate directory from JavaScript/JSX to TypeScript/TSX. #9162 and #9180 provide some tips for performing the migration. Once com

Copied from #7991:

If you look at https://certbot.eff.org/docs/api/certbot.compat.filesystem.html, you'll notice many formatting errors which should be fixed.

That's the bare minimum which I think should be done, but I think we should also see what we can do to avoid these problems from happening in the future. Is there a way we could build the docs in CI and check for these problems?

The following seems to happen on all transform groupby kernels:

df = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
df.groupby([1, 1], axis=1).transform("shift")

results in ValueError: Length mismatch: Expected axis has 2 elements, new values have 3 elements.

I think the issue is in pandas.core.groupby.generic._wrap_transformed_output; this method does not take into account `s