gpu

🚀 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

GGUI crashes when certain keys are pressed (The Windows key, for example).

Relevant code:

https://github.com/taichi-dev/taichi/blob/master/taichi/ui/common/input_handler.h
https://github.com/taichi-dev/taichi/blob/master/taichi/ui/utils/utils.h

It would be great to support all of these keys, or at least add a try-catch to avoid the window from crashing.

At this moment relu_layer op doesn't allow threshold configuration, and legacy RELU op allows that.
We should add configuration option to relu_layer.

usually, after trained model. i save model in cpp format with code:

cat_model.save_model('a', format="cpp")
cat_model.save_model('b', format="cpp")

but when my cpp need to use multi models.

in my main.cpp

#include "a.hpp"
#include "b.hpp"

int main() {
  // do something
  double a_pv = ApplyCatboostModel({1.2, 2.3});  // i want to a.hpp's model here
  double b_pv 

Hi ,

I have tried out both loss.backward() and model_engine.backward(loss) for my code. There are several subtle differences that I have observed , for one retain_graph = True does not work for model_engine.backward(loss) . This is creating a problem since buffers are not being retained every time I run the code for some reason.

Please look into this if you could.

the .pcd file format allows for fields to be extended. this means it can neatly hold data about the label or object of a point. this can be very handy for ML tasks. However, the open3d file io does not appear to be able to read other fields other than the xyz, rgb, normals etc . I haven't been able to find where in the open3d structure the code for the file io pcd loading is implemented to att

Our users are often confused by the output from programs such as zip2john sometimes being very large (multi-gigabyte). Maybe we should identify and enhance these programs to output a message to stderr to explain to users that it's normal for the output to be very large - maybe always or maybe only when the output size is above a threshold (e.g., 1 million bytes?)

Is your feature request related to a problem? Please describe.
I have to place nvim\bin into path environment variable just so that neovide can sense nvim.exe.

Describe the solution you'd like
Add an option to specify nvim path in neovide settings.

https://github.com/brendangregg/FlameGraph

Is your feature request related to a problem? Please describe.

The row_equality_comparator constructor currently accepts a bool to indicate if nulls are considered equal or not. In libcudf, we prefer to use scoped enums instead of bools and we already have a [`

On the time_series branch, this should report an error or something similar since there is no lynx dateset in that folder.

from pycaret.datasets import get_data
y = get_data("lynx", folder="time_series/seasonal")
y = get_data("lynx", folder="time_series/seasonal", index=True)

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.