MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

ryin

#!/bin/bash

# Script for installing tmux on systems where you don't have root access.
# tmux will be installed in $HOME/local/bin.
# It's assumed that wget and a C/C++ compiler are installed.

# exit on error
set -e

TMUX_VERSION=1.8

apaszke

from graphviz import Digraph
import torch
from torch.autograd import Variable, Function

def iter_graph(root, callback):
    queue = [root]
    seen = set()
    while queue:
        fn = queue.pop()
        if fn in seen:

MInner

import datetime
import linecache
import os

import pynvml3
import torch

print_tensor_sizes = True
last_tensor_sizes = set()
gpu_profile_fn = f'{datetime.datetime.now():%d-%b-%y-%H:%M:%S}-gpu_mem_prof.txt'

rmcelreath

# prior - likelihood conflict

library(rethinking)

yobs <- 0

mtt <- ulam(
    alist(
        y ~ dstudent(2,mu,1),
        mu ~ dstudent(2,10,1)

L0SG

import torch
from torch import nn
from torch.autograd import Variable
import torch.nn.functional as F
import torch.optim as optim


# toy feed-forward net
class Net(nn.Module):
    def __init__(self):

ezyang

import torch
from torch.utils._python_dispatch import TorchDispatchMode
from torch.utils._pytree import tree_map
import itertools

# cribbed from https://github.com/albanD/subclass_zoo/blob/main/logging_mode.py

class Lit:
    def __init__(self, s):
        self.s = s

PubuduSaneth

cranmer

#for C++ look here: https://gist.github.com/cranmer/b67830e46d53d5f7cf2d
import ROOT
import numpy as np
def testMomentMorph():

	#Going to make a few statistical models we want to interpolate
	#initialize workspace with some common background part
	w = ROOT.RooWorkspace('w')
	w.factory('Exponential::e(x[-5,15],tau[-.15,-3,0])')
	x = w.var('x')

CamDavidsonPilon

{
  "lines.linewidth": 2.0,
  "examples.download": true,
  "patch.linewidth": 0.5,
  "legend.fancybox": true,
  "axes.color_cycle": [
    "#30a2da",
    "#fc4f30",
    "#e5ae38",
    "#6d904f",