computation is aborted and there is no information about errors, dashboard doesn’t work. I have no idea how to debug it. I will be grateful for any suggestions.
[2021-02-27 10:23:38,372 C 8647 8657] dlmalloc.cc:103: failed to ftruncate file /dev/shm/plasmaTO48oB
[2021-02-27 10:23:38,372 E 8647 8657] logging.cc:415: *** Aborted at 1614417818 (unix time) try "date -d @1614417818" if you are using GNU date ***
[2021-02-27 10:23:38,422 E 8647 8657] logging.cc:415: PC: @ 0x0 (unknown)
[2021-02-27 10:23:38,422 E 8647 8657] logging.cc:415: *** SIGABRT (@0x21c7) received by PID 8647 (TID 0xb23fb3f0) from PID 8647; stack trace: ***
[2021-02-27 10:23:38,423 E 8647 8657] logging.cc:415: @ 0xb6b9a130 (unknown)
Now I try to build ray-1.2.0 again for raspberry ubuntu, it changes architecture from armv7 to aarch64.
For raspbian system architecture is armv7, for ubuntu 64-bit architecture is aarch64
Hmm I am not really familiar with how this wheel works, so it could be hard for me to help. But according to this error; failed to ftruncate file /dev/shm/plasmaTO48oB, I think the issue is ftruncate failed on your arch & wheel. ftruncate(2): truncate file to specified length - Linux man page (Look at the errors section).
Do you think it could be helpful if I make a PR to print the error code here?
@sangcho , I’m not sure what abbreviation is PR but if you have some idea to solve the problem I will be gratefull. In the same time I try to build ray-1.2.0 for aarch64 Ubuntu but the first step is to build pytorch and tensorflow for python 3.8 aarch64.
@sangcho Thank You for explanation (I’m new in python programming and building packages, machine learning is my new hobby when covid has started, I’m metrology enginner not programmer). Now, I continue my work with buildling tensorflow and pytorch wheels for aarch64. I hope ubuntu is better choice for raspberry pi than raspbian if I want use ray.
@sangcho@rliaw After many hours of strugling with raspberry pi 4 and ray-1.2.0 there is success
Now, I try to make script to download my build and install it on raspberry device automatically.
The crucial is:
Using as OS Ubuntu 20.10 with python 3.8 not Raspbian
Installing proper libraries by apt-get
Using proper versions of packages to work with tensorflow2, pytorch and ray. Some packages I have built myself because there were no correct versions available. Tensorflow has over 100 MB so I can’t pull it to github.
@rliaw@sangcho , Thank Yoy for inspiration. Maybe in the futer will be available to install ray directly with pip install command. The idea of using control system with rapberry pi devices (with digital and analog converters and hardware modules) as workers and PC as head is very attractive in my opinion. No need to convert data between raspberry and PC because raspberry becomes part of ML cluster.
The huge advantage is possibility to use easily data from real physical process in real-time training and process modeling.