| """ | |
| The most atomic way to train and inference a GPT LLM in pure, dependency-free Python. | |
| Differences from GPT-2 are minor: rmsnorm instead of layer norm, no biases, square ReLU instead of GeLU nonlinearity. | |
| The contents of this file is everything algorithmically needed to train a GPT. Everything else is just efficiency. | |
| Art project by @karpathy. | |
| """ | |
| import os # for os.path.exists | |
| import math # for math.log, math.exp | |
| import random # for random.seed, random.choices |
| read -p "User please: " -s USER && read -p "Password please: " -s PASS && echo -e "\nBeginning SSH query with user: $USER\n" && for host in '150.164.212.21' '150.164.212.23' '150.164.212.24' '150.164.212.25' '150.164.212.26' '150.164.212.27' '150.164.212.28' '150.164.212.33' '150.164.212.36' '150.164.212.37' '150.164.212.40' '150.164.212.42' '150.164.212.43' '150.164.212.45' '150.164.212.71' '150.164.212.72' '150.164.212.73' '150.164.212.75' '150.164.212.76' '150.164.212.80' '150.164.212.81' '150.164.212.117' '150.164.212.141' '150.164.212.148' '150.164.212.164' '150.164.212.171' '150.164.212.204' '150.164.212.226'; do sshpass -p $PASS ssh -oStrictHostKeyChecking=no $USER@$host 'echo "host:$(hostname) GPU usage: $(nvidia-smi --query-gpu=utilization.gpu,memory.free,memory.total --format=csv,noheader)"' 2> /dev/null; done && PASS="" && USER="" |
Install Tutorial Coppeliasim - Espeleo Simulation
1 - Download CoppeliaSim V4.1.0 for Ubuntu 16.04 (https://coppeliarobotics.com/files/CoppeliaSim_Edu_V4_1_0_Ubuntu16_04.tar.xz). Unzip into a suitable folder.
$ wget -P /tmp https://coppeliarobotics.com/files/CoppeliaSim_Edu_V4_1_0_Ubuntu16_04.tar.xz
$ cd /tmp && tar -xvf CoppeliaSim_Edu_V4_1_0_Ubuntu16_04.tar.xz
$ mv CoppeliaSim_Edu_V4_1_0_Ubuntu16_04 ~/
| license: gpl-3.0 | |
| height: 600 |
| echo linux-image-generic hold | sudo dpkg --set-selections | |
| dpkg -l linux-image-generic | |
| echo linux-headers-generic hold | sudo dpkg --set-selections | |
| dpkg -l linux-headers-generic | |
| sudo apt update | |
| apt-mark showhold |
| #!/usr/bin/env python | |
| import sys, select, termios, tty | |
| def getKey(): | |
| tty.setraw(sys.stdin.fileno()) | |
| rfds, wfds, efds = select.select([sys.stdin], [], [], 0.3) | |
| print(rfds, wfds, efds) | |
| if len(rfds) > 0 or len(wfds) > 0 or len(efds) > 0: | |
| key = sys.stdin.read(1) |
| "dbus-send --print-reply --dest=org.mpris.MediaPlayer2.spotify /org/mpris/MediaPlayer2 org.mpris.MediaPlayer2.Player.PlayPause" XF86AudioPlay | |
| "dbus-send --print-reply --dest=org.mpris.MediaPlayer2.spotify /org/mpris/MediaPlayer2 org.mpris.MediaPlayer2.Player.Stop" XF86AudioStop | |
| "dbus-send --print-reply --dest=org.mpris.MediaPlayer2.spotify /org/mpris/MediaPlayer2 org.mpris.MediaPlayer2.Player.Next" XF86AudioNext | |
| "dbus-send --print-reply --dest=org.mpris.MediaPlayer2.spotify /org/mpris/MediaPlayer2 org.mpris.MediaPlayer2.Player.Previous" XF86AudioPrevious |
| import networkx as nx | |
| import matplotlib.pyplot as plt | |
| import random | |
| import numpy as np | |
| def outliers_modified_z_score(ys): | |
| threshold = 1.5 | |
| median_y = np.median(ys) |
| path_1_2 ={ | |
| 'src': 1, | |
| 'dst': 2, | |
| 'paths': [ | |
| {'path': ['a', 'f', 'b'], 'retransmits': 0}, | |
| {'path': ['a', 'e', 'b'], 'retransmits': 0}, | |
| {'path': ['a', 'e', 'i', 'f', 'b'], 'retransmits': 0}, | |
| ] | |
| } | |
| def calc_precision(rel): | |
| """ | |
| return the precision from a series of hit or miss data | |
| """ | |
| p = [] | |
| hit = 0 | |
| for i in xrange(len(rel)): | |
| if rel[i] > 0: | |
| hit += 1 |