You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
{{ message }}
This repository was archived by the owner on Nov 17, 2023. It is now read-only.
Repository navigation
This repository was archived by the owner on Nov 17, 2023. It is now read-only.
[v1.x] V1.x CD blocked by test_gluon_data.test_list_dataset error #19918
@Zha0q1 Not seen this error before. Looks like it's fixed in default flavor (MKLDNN=1) of MXNet as it fails for "native" but passes in the "cpu" pipeline.
@Zha0q1 Not seen this error before. Looks like it's fixed in default flavor (MKLDNN=1) of MXNet as it fails for "native" but passes in the "cpu" pipeline.
I think it's a flaky test. It also fails on cu 101.
We saw this error before. The problem happens when you make a new data loader while the previous data loader is not yet fully destroyed (including the data it produced in shared memory). Workers in the new data loader inherit those shared memory ndarrays (without increasing the usage counter which exists in the shared memory region itself) and once python's garbage collector decides to destroy them, they decrement the usage counter (and so it gets decremented too much). There are 2 things that may happen then - either the workers destroy the ndarray and the main process gets this error, or the main process does it and then workers get this error and crash, which results in a hang.
I made a small workaround for this in our container by inserting waitall and forcing python gc before the fork. I will make a pr tomorrow with this workaround.
We saw this error before. The problem happens when you make a new data loader while the previous data loader is not yet fully destroyed (including the data it produced in shared memory). Workers in the new data loader inherit those shared memory ndarrays (without increasing the usage counter which exists in the shared memory region itself) and once python's garbage collector decides to destroy them, they decrement the usage counter (and so it gets decremented too much). There are 2 things that may happen then - either the workers destroy the ndarray and the main process gets this error, or the main process does it and then workers get this error and crash, which results in a hang.
I made a small workaround for this in our container by inserting waitall and forcing python gc before the fork. I will make a pr tomorrow with this workaround.
Activity
mseth10 commentedon Feb 18, 2021
@Zha0q1 Not seen this error before. Looks like it's fixed in default flavor (
MKLDNN=1) of MXNet as it fails for "native" but passes in the "cpu" pipeline.Zha0q1 commentedon Feb 18, 2021
I think it's a flaky test. It also fails on cu 101.
In this run three days ealier native also passed.
https://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/restricted-mxnet-cd%2Fmxnet-cd-release-job-1.x/detail/mxnet-cd-release-job-1.x/1487/pipeline
ptrendx commentedon Feb 19, 2021
We saw this error before. The problem happens when you make a new data loader while the previous data loader is not yet fully destroyed (including the data it produced in shared memory). Workers in the new data loader inherit those shared memory ndarrays (without increasing the usage counter which exists in the shared memory region itself) and once python's garbage collector decides to destroy them, they decrement the usage counter (and so it gets decremented too much). There are 2 things that may happen then - either the workers destroy the ndarray and the main process gets this error, or the main process does it and then workers get this error and crash, which results in a hang.
I made a small workaround for this in our container by inserting waitall and forcing python gc before the fork. I will make a pr tomorrow with this workaround.
Zha0q1 commentedon Feb 19, 2021
That's great thanks!
Zha0q1 commentedon Feb 22, 2021
should be fixed now thanks @ptrendx !!