NumPy

🚀 Feature

Add information to this error message which will help an end-user actually figure out what is wrong:
RuntimeError: Expected from <= to to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.)

Motivation

The error message itself told me to ask for an improvement... I cannot find any useful info on thi

I notice that there are still a fair number LGTM alerts, many of which look pretty simple. I wonder if they would be a good source of issues for the next NumPy sprint?

Related to #8006 but the opposite side of the coin: while one can save to_zarr, it is still not possible to give a pathlib.Path object to dask.array.from_zarr, although this is possible withzarr.open.

I see comments suggesting adding this to understand how loops are being handled by numba, and in the their own FAQ (https://numba.pydata.org/numba-doc/latest/user/faq.html)

from llvmlite import binding as llvm
llvm.set_option('','--debug-only=loop-vectorize')

You would then create your njit function and run it, and I believe the idea is that it prints debug information about whether

Is there a way to train a bidirectional RNN (like LSTM or GRU) on trax nowadays?

What's your use case?
In other words, what's your pain point?

Variable names and their icons are shown as vertical header. This

• is ugly,
• doesn't show the selection properly,
• doesn't allow sorting by variable names,
• doesn't allow selection by dragging across a range of variables (though one can drag across rows in the table itself),
• and possibly something else.

<img wi

hi,
if possible, please add these indicators as well:
TDI (Traders Dynamic Index)
chandelier exit
pivot points
BOP (balance of power)
CTM (Chande trend meter)
Coppock Curve
Correlation Coefficient
PMO (DecisionPoint Price Momentum Oscillator)
Ulcer Index
most of them except TDI are available on stockcharts.com
thanks

Description

While using tokenizers.create with the model and vocab file for a custom corpus, the code throws an error and is not able to generate the BERT vocab file

Error Message

ValueError: Mismatch vocabulary! All special tokens specified must be control tokens in the sentencepiece vocabulary.

To Reproduce

from gluonnlp.data import tokenizers
tokenizers.create('spm', model_p

Noting down a comment by @DanJonesOcean on Twitter: https://twitter.com/DanJonesOcean/status/1441392596362874882

In general, having more examples on each xarray page (like the one below) would be good. Then they would come up quickly in function searches:

http://xarray.pydata.org/en/stable/generated/xarray.Dataset.merge.html#xarray.Dataset.merge

Our API docs are generated by the func

Describe the bug
when I try to use sort_values(ignore_index=True) after dropna, it raises TypeError:

a = md.Series([1,3,2,np.nan,np.nan])
a.dropna().sort_values(ignore_index=True).execute()

but I can do it in pandas:

b