We need to be able to run a specific version/commit of TensorFlow and the dependancy requirements for TF are very extreme. We strongly suggest against trying to compile and run on your native computer OS - that way we don't get weird interactions with your OS, compiler toolchain, Python kit, etc. Also, TF really wants to run on a particular version of Linux and chances are you aren't running it.
Instead, we will be using Docker to containerize and separate the TF build so we have a compact, clean, dependable build. Docker is lighter than VMWare/vagrant, and has a very nice 'hub' backend for saving/restoring your images, all for free!
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Signup and log into DockerSign up at https://hub.docker.com/signup
You don't need to pay for an account, but be aware the software images we'll be using are public so don't put any private data in em! |
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Download and Install Desktop DockerDownload Docker software for Windows or Mac, whichever matches your computer |
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TensorFlow needs a lot of computing resourcesGive it as many CPUs and as much RAM as you can spare You need to give it at least 8 GB of RAM or gcc will fail with a very annoying and somewhat confusing error like this (but on some other file) |
ERROR: /root/tensorflow/tensorflow/core/kernels/BUILD:3371:1: C++ compilation of rule '//tensorflow/core/kernels:reduction_ops' failed (Exit 4) gcc: internal compiler error: Killed (program cc1plus) Please submit a full bug report, with preprocessed source if appropriate. See <file:///usr/share/doc/gcc-7/README.Bugs> for instructions. Target //tensorflow/examples/speech_commands:train failed to build Use --verbose_failures to see the command lines of failed build steps. INFO: Elapsed time: 6058.951s, Critical Path: 3278.24s INFO: 2606 processes: 2606 local. FAILED: Build did NOT complete successfully FAILED: Build did NOT complete successfully
Open a command terminal and try to login, use the same username/password as from the site
OK you're ready to go!
