This is a companion piece to my instructions on building TensorFlow from source. In particular, the aim is to install the following pieces of software
on an Ubuntu Linux system, in particular Ubuntu 20.04.
| #!/usr/bin/env python3 | |
| import sys | |
| import eventlet | |
| eventlet.monkey_patch(socket=True) | |
| from eventlet.timeout import Timeout | |
| import requests | |
| ;; Hardware IDs | |
| HWID_LEGS equ 0x1 | |
| HWID_LASER equ 0x2 | |
| HWID_LIDAR equ 0x3 | |
| HWID_KEYBOARD equ 0x4 | |
| HWID_DRILL equ 0x5 | |
| HWID_INV equ 0x6 | |
| HWID_RNG equ 0x7 | |
| HWID_CLOCK equ 0x8 | |
| HWID_HOLO equ 0x9 |
The official instructions on installing TensorFlow are here: https://www.tensorflow.org/install. If you want to install TensorFlow just using pip, you are running a supported Ubuntu LTS distribution, and you're happy to install the respective tested CUDA versions (which often are outdated), by all means go ahead. A good alternative may be to run a Docker image.
I am usually unhappy with installing what in effect are pre-built binaries. These binaries are often not compatible with the Ubuntu version I am running, the CUDA version that I have installed, and so on. Furthermore, they may be slower than binaries optimized for the target architecture, since certain instructions are not being used (e.g. AVX2, FMA).
So installing TensorFlow from source becomes a necessity. The official instructions on building TensorFlow from source are here: ht
