numpy

🐛 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

Picking up from #15731, there are many places in numpy where we do something like:

try:
    something_which_throws_typeError
except TypeError:
    raise ValueError("a clearer explanation of what went wrong")

It would produce a marginally clearer error if we could change these to use traceback chaining. Our two options are either:

The inner error provides valuable infor

The documentation in the Joins section https://docs.dask.org/en/latest/dataframe-joins.html has code blocks but they aren't interactive and therefore not as useful.

I think the documentation would benefit from an interactive example with use of real data (or data from the demo API).

I had a quick rummage of the tutorial (h

Reporting a bug

[x]

Well, Gumbel Distribution is magical. Basically, given a sequence of K logits, i.e., "\log a_1, \log a_2, ..., \log a_K" and K independent gumbel random variables, i.e., "g_1, g_2, ..., g_K". We have

\argmax_i \log a_i + g_i ~ Categorical({a_i / sum(a)})

This gives you a very simple way to sampl

Support Series.median()

What happened:
xr.DataArray([1], coords=[('onecoord', [2])]).sel(onecoord=2).to_dataframe(name='name') raise an exception ValueError: no valid index for a 0-dimensional object

What you expected to happen:

the same behavior as: xr.DataArray([1], coords=[('onecoord', [2])]).to_dataframe(name='name')

Anything else we need to know?:

I see that the array after the select

Aug	SEP	Oct
	13
2019	2020	2021

numpy

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🐛 Bug

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