Zsh: illegal hardware instruction perceptilabs

I am trying to install perceptilabs, and the rest code works but whenever I try to just type perceptilabs to launch the browser I just get the output:
zsh: illegal hardware instruction perceptilabs
I used anaconda
I am on a mac
I have no idea how to fix it, I saw a similar answer with tensorflow when researching this problem, but I am not sure how to use that
Any help would be much appreciated

Hi @Thomas_I

I can’t help but I can make a suggestion that will help the PercepiLabs guys help you…

Can you copy/paste or attach the contents of the terminal/console where the PL server is?

If you could try that with perceptilabs -v=3 (a debug setting that increases verbosity) that might help too.

What was the source for TF β€œanswer” you saw? The more info you can give the easier it will be to nail down :slight_smile:

And Welcome to the club :smiley:

(base) thomasnabilissa@dhcp-10-8-041-249 ~ % conda create -n myenv python=3.8
Collecting package metadata (current_repodata.json): done
Solving environment: done

Package Plan

environment location: /Users/thomasnabilissa/opt/anaconda3/envs/myenv

added / updated specs:
- python=3.8

The following NEW packages will be INSTALLED:

ca-certificates pkgs/main/osx-64::ca-certificates-2021.9.30-hecd8cb5_1
certifi pkgs/main/osx-64::certifi-2021.10.8-py38hecd8cb5_0
libcxx pkgs/main/osx-64::libcxx-12.0.0-h2f01273_0
libffi pkgs/main/osx-64::libffi-3.3-hb1e8313_2
ncurses pkgs/main/osx-64::ncurses-6.2-h0a44026_1
openssl pkgs/main/osx-64::openssl-1.1.1l-h9ed2024_0
pip pkgs/main/osx-64::pip-21.2.4-py38hecd8cb5_0
python pkgs/main/osx-64::python-3.8.12-h88f2d9e_0
readline pkgs/main/osx-64::readline-8.1-h9ed2024_0
setuptools pkgs/main/osx-64::setuptools-58.0.4-py38hecd8cb5_0
sqlite pkgs/main/osx-64::sqlite-3.36.0-hce871da_0
tk pkgs/main/osx-64::tk-8.6.11-h7bc2e8c_0
wheel pkgs/main/noarch::wheel-0.37.0-pyhd3eb1b0_1
xz pkgs/main/osx-64::xz-5.2.5-h1de35cc_0
zlib pkgs/main/osx-64::zlib-1.2.11-h1de35cc_3

Proceed ([y]/n)? y

Preparing transaction: done
Verifying transaction: done
Executing transaction: done

To activate this environment, use

$ conda activate myenv

To deactivate an active environment, use

$ conda deactivate

(base) thomasnabilissa@dhcp-10-8-041-249 ~ % conda activate myenv
(myenv) thomasnabilissa@dhcp-10-8-041-249 ~ % pip install perceptilabs
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Installing collected packages: urllib3, pyasn1, idna, charset-normalizer, wcwidth, vine, six, rsa, requests, pyasn1-modules, oauthlib, cachetools, typing-extensions, requests-oauthlib, python-dateutil, pycparser, protobuf, prompt-toolkit, numpy, MarkupSafe, jmespath, google-auth, click, amqp, wrapt, Werkzeug, toolz, termcolor, tensorboard-plugin-wit, tensorboard-data-server, sqlparse, smmap, pyyaml, pytz, pyparsing, pillow, onnx, multidict, markdown, locket, kombu, kiwisolver, jinja2, itsdangerous, isodate, grpcio, google-auth-oauthlib, cycler, cloudpickle, click-repl, click-plugins, click-didyoumean, cffi, botocore, billiard, asgiref, absl-py, zipp, yarl, uamqp, typeguard, tornado, tifffile, threadpoolctl, tensorflow-estimator, tensorboard, starlette, sentry-sdk, scipy, s3transfer, PyWavelets, pyrsistent, pynacl, PyJWT, pydantic, prometheus-client, partd, pandas, opt-einsum, onnxconverter-common, networkx, msrest, mlagents-envs, matplotlib, keras-preprocessing, keras-nightly, joblib, imageio, humanize, h5py, h11, gym, google-pasta, gitdb, gast, fsspec, flatbuffers, flask, fire, Django, Deprecated, dask, cwcwidth, cryptography, chardet, celery, brotli, blinker, blessings, azure-core, attrs, async-timeout, astunparse, websockets, websocket-client, waitress, uvicorn, tf2onnx, tensorflow-addons, tensorflow, Send2Trash, scikit-learn, scikit-image, retrying, redis, pyzmq, pygments, PyGithub, psycopg2-binary, psutil, packaging, opencv-python, mixpanel, keras2onnx, keras-unet-collection, jsonschema, importlib-metadata, gym-unity, greenlet, gputil, GitPython, flower, flask-cors, flask-compress, fastapi, djangorestframework, django-request-logging, django-http-exceptions, django-cors-headers, curtsies, boto3, boto, boltons, azure-storage-blob, azure-eventhub, astor, aiohttp, perceptilabs
Successfully installed Deprecated-1.2.13 Django-3.2 GitPython-3.1.24 MarkupSafe-2.0.1 PyGithub-1.55 PyJWT-2.3.0 PyWavelets-1.1.1 Send2Trash-1.8.0 Werkzeug-2.0.2 absl-py-0.15.0 aiohttp-3.7.4 amqp-5.0.6 asgiref-3.4.1 astor-0.8.1 astunparse-1.6.3 async-timeout-3.0.1 attrs-21.2.0 azure-core-1.19.0 azure-eventhub-5.1.0 azure-storage-blob-12.6.0 billiard-3.6.4.0 blessings-1.7 blinker-1.4 boltons-21.0.0 boto-2.49.0 boto3-1.19.2 botocore-1.22.2 brotli-1.0.9 cachetools-4.2.4 celery-5.1.2 cffi-1.15.0 chardet-3.0.4 charset-normalizer-2.0.7 click-7.1.2 click-didyoumean-0.3.0 click-plugins-1.1.1 click-repl-0.2.0 cloudpickle-2.0.0 cryptography-35.0.0 curtsies-0.3.10 cwcwidth-0.1.5 cycler-0.10.0 dask-2.6.0 django-cors-headers-3.10.0 django-http-exceptions-1.4.0 django-request-logging-0.7.3 djangorestframework-3.12.4 fastapi-0.68.0 fire-0.4.0 flask-2.0.2 flask-compress-1.9.0 flask-cors-3.0.10 flatbuffers-1.12 flower-1.0.0 fsspec-2021.10.1 gast-0.4.0 gitdb-4.0.9 google-auth-2.3.0 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 gputil-1.4.0 greenlet-1.1.2 grpcio-1.34.1 gym-0.21.0 gym-unity-0.27.0 h11-0.12.0 h5py-3.1.0 humanize-3.12.0 idna-3.3 imageio-2.9.0 importlib-metadata-4.8.1 isodate-0.6.0 itsdangerous-2.0.1 jinja2-3.0.2 jmespath-0.10.0 joblib-1.1.0 jsonschema-3.2.0 keras-nightly-2.5.0.dev2021032900 keras-preprocessing-1.1.2 keras-unet-collection-0.1.10 keras2onnx-1.7.0 kiwisolver-1.3.2 kombu-5.1.0 locket-0.2.1 markdown-3.3.4 matplotlib-3.4.2 mixpanel-4.7.0 mlagents-envs-0.27.0 msrest-0.6.21 multidict-5.2.0 networkx-2.6.3 numpy-1.19.2 oauthlib-3.1.1 onnx-1.9.0 onnxconverter-common-1.8.1 opencv-python-4.5.4.58 opt-einsum-3.3.0 packaging-21.0 pandas-1.3.4 partd-1.2.0 perceptilabs-0.12.25 pillow-7.0.0 prometheus-client-0.11.0 prompt-toolkit-3.0.21 protobuf-3.19.0 psutil-5.8.0 psycopg2-binary-2.9.1 pyasn1-0.4.8 pyasn1-modules-0.2.8 pycparser-2.20 pydantic-1.8.2 pygments-2.10.0 pynacl-1.4.0 pyparsing-3.0.0 pyrsistent-0.18.0 python-dateutil-2.8.2 pytz-2021.3 pyyaml-6.0 pyzmq-22.3.0 redis-3.5.3 requests-2.26.0 requests-oauthlib-1.3.0 retrying-1.3.3 rsa-4.7.2 s3transfer-0.5.0 scikit-image-0.17.2 scikit-learn-1.0 scipy-1.7.1 sentry-sdk-1.4.3 six-1.15.0 smmap-5.0.0 sqlparse-0.4.2 starlette-0.14.2 tensorboard-2.7.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.0 tensorflow-2.5.0 tensorflow-addons-0.13.0 tensorflow-estimator-2.5.0 termcolor-1.1.0 tf2onnx-1.7.2 threadpoolctl-3.0.0 tifffile-2021.10.12 toolz-0.11.1 tornado-6.1 typeguard-2.13.0 typing-extensions-3.7.4.3 uamqp-1.4.3 urllib3-1.25.10 uvicorn-0.15.0 vine-5.0.0 waitress-2.0.0 wcwidth-0.2.5 websocket-client-1.2.1 websockets-10.0 wrapt-1.12.1 yarl-1.7.0 zipp-3.6.0
(myenv) thomasnabilissa@dhcp-10-8-041-249 ~ % perceptilabs -v=3
zsh: illegal hardware instruction perceptilabs -v=3

Thanks - let’s see what the PL guys come up with now!

Hi @Thomas_I, thanks for the log!
Are you by chance using the M1 chip in your Mac?

We had a few people have this issue over the summer, but unfortunately it seemed to be on TensorFlows side and wasn’t much we could do to solve it.
To double check, you can try importing just TensorFlow and see if that works:

$ python
>> import tensorflow as tf

All the best,
Robert

Hi @Thomas_I

(@robertl for info)

I did some looking around and I see that there are a lot of issues with TF 2.5 on M1 - and that Apple has a private fork of TF so the TF team aren’t involved and can’t do anything about it.

However, I found this StackOverflow post that suggests an alternative to try for this: β€œI had a related problem with using TensorFlow on a M1 Mac. Solution is to use a universal arm version of TF.”

Do let us know if you can try it and whether it helps!

Sorry for the bother, I realize now that the issue is that perceptilabs is not natively supported with Apple computers with M1. I had a similar experience when trying to work with MySQL, figuring out a workaround is an absolute pain that can be easily sidestepped by working with the intended hardware. I intend to use that shortcut instead of metaphorically trying to stick a square inside of a circular hole. Thank you for your help, I look forward to officially joining the community!

Hey @Thomas_I

:smiley: No worries - we’re looking forward to hearing what you do with PL and hope you can share the journey with us!

I expect M1 will align better in future, but to be fair to the PL guys, I think it’s an Apple/TensorFlow/M1 issue rather than a PL/M1 issue :wink:

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