Open Kup3a opened 5 years ago
UPD -prefetch_size 16 didn`t help
Can report similar issue locally with cpu only version of tensorflow and: tensorflow 1.13.1 bert-as-a-service 1.8.3
INFO:tensorflow:Calling model_fn.
I:VENTILATOR:[__i:_ru:148]:new config request req id: 1 client: b'f01b84db-4dd7-423e-b1bc-c9ab46a470df'
I:SINK:[__i:_ru:320]:send config client b'f01b84db-4dd7-423e-b1bc-c9ab46a470df'
I:VENTILATOR:[__i:_ru:164]:new encode request req id: 2 size: 3 client: b'f01b84db-4dd7-423e-b1bc-c9ab46a470df'
I:SINK:[__i:_ru:317]:job register size: 3 job id: b'f01b84db-4dd7-423e-b1bc-c9ab46a470df#2'
Nothing seems to happen after this point.
Also max_batch_size 16 did not help
how about -prefetch_size 0
@Kup3a Have you found the solution yet ? I am facing the same issue. The server never seems to start in a docker with a HTTP request, However locally it works fine.
@hanxiao do you have the fix for the cpu only version.
Using kaggle/python as base image fixed the problem and should work for everyone. But not sure what was the root cause of the issue. It seems zeromq was unable to bind the sockets.
Prerequisites
bert-as-service
?README.md
?README.md
?System information
On my local machine everything is alright, but i can`t run bert inside docker.
bert-as-service
version: 1.8.1Description
I'm using this command to start the server:
test_bert_local previously built from Dockerfile:
inside entrypoint.sh
server shows
server can response to status/server with (via curl)
but after calling /encode (via curl) i see this
and server is never responding. Locally everything is working fine, after about one minute i see 'ready' from WORKER[0] and /encode is responding normally.
Also i noticed, that during local-run bert is actively consuming 1cpu before he writes 'ready'. In docker-case htop shows zero cpu-consuming.
Thank you for reading. I'll add any extra info if needed.