Running Inception causes Server returned unexpected status code: 500 - signal: illegal instruction (core dumped)

[burf2000]

Expected Behaviour

Running the example code should return [{"name": "great white shark", "score": 0.5343291759490967}, {"name": "tiger shark", "score": 0.09276486188173294}, {"name": "grey whale", "score": 0.05899052694439888}, {"name": "sea lion", "score": 0.05105864629149437}, {"name": "hammerhead", "score": 0.019910583272576332}, {"name": "sturgeon", "score": 0.013177040033042431}, {"name": "stingray", "score": 0.00763126602396369}, {"name": "electric ray", "score": 0.006749240681529045}, {"name": "killer whale", "score": 0.005086909048259258}, {"name": "ice bear", "score": 0.003828041721135378}]

Current Behaviour

URL=https://upload.wikimedia.org/wikipedia/commons/6/61/Humpback_Whale_underwater_shot.jpg echo $URL | faas-cli invoke inception
Server returned unexpected status code: 500 - signal: illegal instruction (core dumped)

Possible Solution

Steps to Reproduce (for bugs)

I installed the function via the function store

Context

Your Environment

Dual Intel(R) Xeon(R) CPU L5410 @ 2.33GHz
128GB DDR2

• Docker version docker version (e.g. Docker 18.06 ):
  Client:
  Version: 18.09.1
  API version: 1.39
  Go version: go1.10.6
  Git commit: 4c52b90
  Built: Wed Jan 9 19:35:23 2019
  OS/Arch: linux/amd64
  Experimental: false

Server: Docker Engine - Community
Engine:
Version: 18.09.1
API version: 1.39 (minimum version 1.12)
Go version: go1.10.6
Git commit: 4c52b90
Built: Wed Jan 9 19:02:44 2019
OS/Arch: linux/amd64
Experimental: false

• Are you using Docker Swarm or Kubernetes (FaaS-netes)?
  Swarm

• Operating System and version (e.g. Linux, Windows, MacOS):
  Ubuntu 16.04

• How much RAM is available on your nodes?
  422d6498a3fb inception.1.4knd787uo9z1r0wdt8s5ptsa8 0.00% 1.258MiB / 123.5GiB 0.00% 15.1kB / 6.32kB 56.9MB / 0B 7

• Are you running on x86_64 or ARM?
  x86_64

• Link to your project or a code example to reproduce issue:
  Its the code here

• Please also follow the [troubleshooting guide]

[burf2000]

The issue is due to The TensorFlow library was compiled to use AVX instructions, but these aren't available on your machine.

pip install tensorflow==1.5