CUDA

Reporting a bug

• I have tried using the latest released version of Numba (most recent is
  visible in the change log (https://github.com/numba/numba/blob/master/CHANGE_LOG).
• I have included a self contained code sample to reproduce the problem.
  i.e. it's possible to run as 'python bug.py'.

(a static analyzer bug report)

In file numba/np/ufunc/omppool.cpp, `numba/np

Problem: the approximate method can still be slow for many trees
catboost version: master
Operating System: ubuntu 18.04
CPU: i9
GPU: RTX2080

Would be good to be able to specify how many trees to use for shapley. The model.predict and prediction_type versions allow this. lgbm/xgb allow this.

Describe the bug
When compiling v0.13.0 build fails with

/home/zannzetsu/open3d/src/open3d/cpp/open3d/visualization/rendering/filament/FilamentEntitiesMods.cpp:212:22:   required from here
/usr/include/fmt/core.h:1579:7: error: static assertion failed: Cannot format an argument. To make type T formattable provide a formatter<T> specialization: https://fmt.dev/latest/api.html#udt
 157

For feature engineering tasks, I'd like to be able to determine whether a datetime is the beginning or end of a year, like I can in pandas.

import pandas as pd
​
s = pd.Series(["2021-02-27", "2020-03-31"], dtype="datetime64[ms]")
s.dt.is_year_end
0    False
1    False
dtype: bool

import pandas as pd
​
s = pd.Series(["2021-01-01", "2020-04-01"], dtype="datet

Current implementation of join can be improved by performing the operation in a single call to the backend kernel instead of multiple calls.

This is a fairly easy kernel and may be a good issue for someone getting to know CUDA/ArrayFire internals. Ping me if you want additional info.

We're seeing a lot of warnings on Linux, host compiler GCC 9.3.0 with -Wconversion.

For a basic example, compile:

#include <thrust/device_vector.h>
int main() {
  thrust::device_vector<int> a;
  return 0;
}

With: nvcc main.cu -Xcompiler=-Wconversion.

This will result in around 1000 lines of output warnings.
Tested with the Thrust versions in CUDA 11.0, 11.3, and the la

请问可以直接training tmfile出来吗? 因为tengine-convert-tool covert 会有error

tengine-lite library version: 1.4-dev
Get input tensor failed

或是有例子能training出下面tmfile 呢?
![Screenshot from 2021-05-27 07-01-46](https://user-images.githubusercontent.com/40915044/11

Report needed documentation

Report needed documentation
While the estimator guide offers a great breakdown of how to use many of the tools in api_context_managers.py, it would be helpful to have information right in the docstring during development to more easily understand what is actually going on in each of the provided functions/classes/methods. This is particularly important for

I often use -v just to see that something is going on, but a progress bar (enabled by default) would serve the same purpose and be more concise.

We can just factor out the code from futhark bench for this.