Skip to content
#

gpu

Here are 2,663 public repositories matching this topic...

kumpera
kumpera commented Jan 19, 2022

🐛 Describe the bug

Usage of RRefContext::handleException in torch/csrc/distributed/rpc/rref_context.cpp is wrong when the future has an error.

RRefContext::handleException uses TORCH_CHECK which throws.

Callers of RRefContext::handleException don't expect that and run code after it without any guarding.

Versions

master

cc @pietern @mrshenli @pritamdamania87

ailzhang
ailzhang commented Dec 30, 2021

As shown in taichi-dev/taichi#3910, replacing property with simple attributes can speedup python part of taichi a lot.
Lessons learned is that we should avoid using @property when applicable since it's expensive. So let's review the usage of @property in our python codebase and replace them as much as possible.

Here's a list of simple grep in our codebase showing

ayulockin
ayulockin commented Dec 1, 2021

I am working on creating a WandbCallback for Weights and Biases. I am glad that CatBoost has a callback system in place but it would be great if we can extend the interface.

The current callback only supports after_iteration that takes info. Taking inspiration from XGBoost callback system it would be great if we can have before iteration that takes info, before_training, and `after

rsn870
rsn870 commented Aug 21, 2020

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.

solardiz
solardiz commented Jul 19, 2019

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?)

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

  • Updated Jan 30, 2022
  • Jupyter Notebook
miguelusque
miguelusque commented Jan 15, 2022

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

While porting some code from Pandas to cuDF, I have noticed that cuDF series do not support unstack method.
As an additional request, It would be great if fill_values could be supported in both cudf.DataFrame.unstack and cudf.Series.unstack methods. Thanks!

Describe the solution you'd like
To have that meth

wgpu
jinleili
jinleili commented Jan 25, 2022

Test device: Google Nexus 5x(Android 8.1.0)
Backend: VULKAN

2022-01-25 10:55:31.018 27110-27110/name.jinleili.wgpu W/wgpu_hal::vulkan::ada..: sample_rate_shading feature is not supported, hiding adapter: Adreno (TM) 418
2022-01-25 10:55:31.019 27110-27110/name.jinleili.wgpu A/libc: Fatal signal 6 (SIGABRT), code -6 in tid 27110 (e.jinleili.wgpu), pid 27110 (e.jinleili.wgpu)

<deta

Improve this page

Add a description, image, and links to the gpu topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the gpu topic, visit your repo's landing page and select "manage topics."

Learn more