Seems to be a common problem... the latest version uses a later tfjs engine so the binary needs also to be updated/reinstalled. You have two options - either completely uninstall the node so and then reinstall it - so the binary gets re-installed and rebuilt - or to drop back a level to the previous version.
Ok, thank you ...
Can you tell me how can back to the previous version?
cd ~/.node-red npm i firstname.lastname@example.org
or whatever version you want/need
then restart node-red
Thank you ....
Did not work for me when I tried that option. Reverting back to 1.0.2 works fine but drawback could be if the newer tjfs engine brings some improvements
EDIT: RPi 4, Node-RED version 3.0.0 beta 2
I think the old one has some potential vulnerabilities .
The same for me.
I came back to the previous version (1.0.2) and now the node works fine ...
After installing 1.0.3 - can someone try
cd ~/.node-red npm rebuild @tensorflow/tfjs-node --build-from-source
then restart node-red ( node-red-reload )
and report back... thanks
Hello, it did not help, see errors from log below. So now NR just keeps on restarting. But I see that the node at least tries to load the model, that did not happen before. Don't know if this helps
Best regards, Walter
2022-06-06 07:24:18.315788: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 1080000 exceeds 10% of free system memory. 2022-06-06 07:24:18.366906: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 1080000 exceeds 10% of free system memory. 6 Jun 07:24:18 - [red] Uncaught Exception: 6 Jun 07:24:18 - [error] TypeError: tf.engine(...).makeTensorFromTensorInfo is not a function at NodeJSKernelBackend.createOutputTensor (/home/pi/.node-red/node_modules/@tensorflow/tfjs-node/dist/nodejs_kernel_backend.js:153:28) at NodeJSKernelBackend.executeSingleOutput (/home/pi/.node-red/node_modules/@tensorflow/tfjs-node/dist/nodejs_kernel_backend.js:215:21) at Object.kernelFunc (/home/pi/.node-red/node_modules/@tensorflow/tfjs-node/dist/kernels/Cast.js:33:24) at kernelFunc (/home/pi/.node-red/node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js:4541:32) at /home/pi/.node-red/node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js:4602:27 at Engine.scopedRun (/home/pi/.node-red/node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js:4406:23) at Engine.runKernelFunc (/home/pi/.node-red/node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js:4598:14) at Engine.runKernel (/home/pi/.node-red/node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js:4470:21) at cast_ (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:12204:19) at cast__op (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:11577:29) at executeOp$1 (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:28129:21) at /home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:28236:65 at /home/pi/.node-red/node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js:4396:22 at Engine.scopedRun (/home/pi/.node-red/node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js:4406:23) at Engine.tidy (/home/pi/.node-red/node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js:4395:21) at Object.tidy (/home/pi/.node-red/node_modules/@tensorflow/tfjs-core/dist/tf-core.node.js:10327:19) at /home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:28236:39 at executeOp (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:28252:7) at _loop_1 (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:28978:31) at GraphExecutor.processStack (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:29004:13) at GraphExecutor.<anonymous> (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:28930:41) at step (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:147:27) at Object.next (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:96:53) at /home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:89:71 at new Promise (<anonymous>) at __awaiter (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:75:12) at GraphExecutor.executeWithControlFlow (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:28899:16) at GraphExecutor.<anonymous> (/home/pi/.node-red/node_modules/@tensorflow/tfjs-converter/dist/tf-converter.node.js:28849:51) nodered.service: Main process exited, code=exited, status=1/FAILURE nodered.service: Failed with result 'exit-code'.
@krambriw - are you running 32bit or 64bit version of the OS ?
(sadly I don't have a Pi4 - but the rebuild fixes it for me on a 32bit Pi3... will try 64bit later)
Oh yes, that could be the reason, I'm running 64bit on this RPi4 (just tell me if I can help in testing)
Just tried installing 1.0.3 on RPi-4B (I assume I'm running a 32-bit OS) as it runs fine.
My Pi 4 with os Raspbian OS - 32bit ....
@Giamma - have you tried the rebuild as suggested above ?
Ehm, no .....
I wanted to try but when I read about the problems (@krambriw), I let it go.
My raspberry manages all my home automation, light, alarm, conditioning, irrigation system, if raspberry stopping, my wife may kill me ....
two suggestions, (1) get a another Pi for development (2) make a backup copy of your SD card.
Looks like it is an as yet unresolved issue with the underlying TFJS support for arm64 - [tjfs-node] Unsupported system: cpu-linux-arm64 in raspberry pi 4 · Issue #5937 · tensorflow/tfjs · GitHub
so stick to 32 bit on Pi for now
Yes, and I have to correct myself, I also had a problem on another RPi4 running 32 bit OS. In this case I suspected a conflict with another contribution, the "node-red-contrib-tensorflow", I had that installed as well. Once I uninstalled it, I could rebuild and now 1.0.3 works fine in my RPi4 (running 32 bit OS)
I tried and ........................
works fine !
Thank you .......
Hi, I ran into this issue after updating the tf-coco-ssd node yesterday. I was looking for a solution and found this thread. I am on a RPI4B and can confirm @dceejay solution above works perfectly. Thankyou.