rubbberrabbit opened a new issue, #21119: URL: https://github.com/apache/incubator-mxnet/issues/21119
## Description Segment fault when calculating data located at different GPU. Most of the time, manipulating data located on different devices will give clear exceptions to tell users to deep copy data to the same device before manipulating. But I found that simply adding two ndarray data at different GPU will just cause segment fault, which may indicate the add operator can not handle the condition well nor give a reasonable exception report. ### Error Message Segment Fault ## To Reproduce I run this script on MxNet1.9.1 with two RTX3090 GPU. `from mxnet import np,npx import mxnet.gluon.nn as nn npx.set_np() X = np.ones((1, 10),ctx=npx.gpu(0)) Y = np.ones((1, 10),ctx=npx.gpu(1)) C = X + Y print(C)` ### Steps to reproduce (Paste the commands you ran that produced the error.) run the code script ## What have you tried to solve it? ## Environment ***We recommend using our script for collecting the diagnostic information with the following command*** `curl --retry 10 -s https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py | python3` <details> <summary>MxNet1.9.1 CUDA11.2 with two RTX3090 GPU.</summary> ``` # Paste the diagnose.py command output here ``` </details> -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@mxnet.apache.org.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@mxnet.apache.org For additional commands, e-mail: issues-h...@mxnet.apache.org
