- Latest firmware downloaded to board
- Successful model generation
Classifier fails to run with output below
Interval: 0.06 ms.
Frame size: 32000
Sample length: 2000 ms.
No. of classes: 4
Starting inferencing, press 'b' to break
Starting inferencing in 2 seconds...
ERR: cmvnw failed (-1002)
ERR: Failed to run DSP process (-1002)
ERR: Failed to run classifier (-5)
Hi @mcallistertad This is an out of memory error when running the model. You can up the frame length / frame stride a bit in your DSP block to make it use less memory.
I’m getting the same error but I’m not running an audio DSP.
Is there any similar trick to lower memory usage in Spectral Analysis and/or Flatten?
@SpirosMakris Typically flatten / spectral analysis blocks use a lot less RAM, so should be less of an issue on this board. Which of your projects does this refer to?
I though it was a RAM issue, but I’m not so sure now.
I had multiple DSP blocks (1 spectral, 2 flatten) and no matter how I configured them I got the “out of ram” ERR: DSP (-5)/Classifier(-1002) message on the board (I thing these are the error numbers). Although I’m pretty sure there’s like 150k of free RAM left on the ESP.
When I remove the extra DSPs and fed all of my features through a single spectral DSP it runs, but I’m not so sure that feeding 3 different sensor readings in to a single DSP is good for accuracy.
The project is: https://studio.edgeimpulse.com/studio/31046
@SpirosMakris Ah, yeah, this is a bug that pops up sometimes. There are issues with feeding some axis into one DSP block, and other axis into another. We have a tracking bug for it, but can’t provide a date for this to be fixed yet.
I think just feeding into the single DSP block should be fine for now.
Thanks @janjongboom !
I understand. That’s what I did in the end.
Hoping this will be fixed soon.
Thanks @janjongboom. Adjusting the frame length/ stride did the job and it’s running on the hardware now.
As an aside, is there a method for predicting memory usage before the binary is generated for the target hardware? A warning or something would be useful.
Yeah we have all that data already available in the backend, but we don’t expose it yet. Good suggestion.
@SpirosMakris We have a patch ready, hope to release this next week (anything that touches core DSP code requires some extensive testing on device ).
Hey @janjongboom, glad to hear this is being fixed. Is there anyplace I could look for status updates on this, like a github issue or a log?
Hi, our GH issues are not public unfortunately, but I’ll update this forum post once released - we’re investigating flash size increase on one of our targets with the patch.
Thanks @janjongboom! I’ll keep an eye on this!
This has now been resolved!
Thanks for the update @janjongboom!