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?

Motivated by huggingface/transformers#12789 in Transformers, one welcoming change would be replacing assertions with proper exceptions. The only type of assertions we should keep are those used as sanity checks.

Currently, there is a total of 87 files with the assert statements (located under datasets and src/datasets), so when working on this, to manage the PR s

Talking to a user recently, they were confused about how to pass divisions= in set_index. Specifically, they missed that the list had to have N+1 elements in it, and the N+1th element was the upper bound for the last partition.

The API docs currently link to https://docs.dask.org/en/latest/dataframe-design.html#partitions, which does describe this in words, but takes some close reading to g

I believe this is undocumented behaviour.

import numba as nb


@nb.njit
def f1():
    for i in nb.prange(1):
        print(type(i))  # >>> int64


@nb.njit(parallel=True)
def f2():
    for i in nb.prange(1):
        print(type(i))  # >>> uint64


f1()
f2()

This caused a nasty bug in my own code that was hard to debug as the problem did not exist without `parallel=Tr

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

环境

1.系统环境：

• Ubuntu 20.04.2 LTS x86_64
• GLIBCXX: 3.4.28 (libstdc++.so.6.0.28)
• GPU:
  

2.MegEngine版本：1.6.0rc1
3.python版本：Python 3.8.10

The program stuck at net.load when I was trying to use the MegFlow. I wait for more than 10min and there is no sign of finishing it.

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