Abhishek Sharma shaabhishek

linux: sort -u filename to remove duplicates from file

linux: use LC_ALL=C x ... instead of x ... to speed up x in {grep, sed, awk, sort}

latex: use package and command bm for bold math symbols

linux: awk '{print $1}' your_file | sort | uniq | wc -l to get unique counts for a column in a file

slurm: sacct --starttime 2022-09-01 --format=User,JobID,Jobname,partition,state,time,start,end,elapsed,MaxRss,MaxVMSize,nnodes,ncpus,nodelist for list all jobs since a specific data

DatasetAllocator:

Helps create the flattened representation of the timeseries tensor from the raw files

DatasetAllocator.record: 1.

Step 1: Install Anaconda compatible with RHEL 6

The file I used was Anaconda3-2020.11-Linux-x86_64.sh from https://repo.anaconda.com/archive/

wget https://repo.anaconda.com/archive/Anaconda3-2020.11-Linux-x86_64.sh
bash Anaconda3-2020.11-Linux-x86_64.sh

Step 2: Create a new environment.

I tried lots of older and newer versions of python but 3.7.0 is the one that worked for me. The patchelf is necessary for the next step.

	name: environment-name
	channels:
	- pytorch
	- defaults
	- anaconda
	dependencies:
	- numpy
	- pandas
	- pytorch
	# - torchvision

	## imports and other stuff

	# Boilerplate for setting things up
	query_args = {'dbname': dbname, 'host': host, 'port': port, 'user': dbusername}
	conn = psycopg2.connect(**query_args)
	cur = conn.cursor()
	cur.execute('SET search_path to ' + schema_name)

	# Setup the query- note it is ALMOST the same as the sql file's query
	query = \

	#questions to answer
	# 1. Do the following sequences give the same hidden states: pad-rnn-hidden & pack-rnn-pad-hidden
	# 2. does the birnn use the (hidden states computed in the forward states) to
	# compute the (hidden states computed in the backward direction)


	import torch
	import torch.nn as nn
	import torch.nn.utils.rnn as rnnutils

	\ProvidesPackage{mystyle}

	\usepackage[utf8]{inputenc}
	\usepackage{amsmath, amssymb, bm}
	\usepackage{mathtools} % for DeclarePairedDelimiter command
	\usepackage{graphicx}
	\usepackage{subcaption} %allows drawing subfigures

	% Set page size and margins
	% Replace `letterpaper' with`a4paper' for UK/EU standard size

	from urllib.request import urlretrieve
	from pathlib import Path
	import time
	import random

	slides_dir = Path('/blablabla/CS590M/slides')

	url = lambda n: f"https://blabla.com/slecture{n:02}h.pdf"
	fname = lambda n: slides_dir / f"slecture{n:02}h.pdf"

	########### INSTALL ###########
	# !pip install --upgrade cmdstanpy
	import os
	import urllib.request
	import shutil
	# Install pre-built CmdStan binary
	# (faster than compiling from source via install_cmdstan() function)
	tgz_file = 'colab-cmdstan-2.23.0.tar.gz'
	tgz_url = 'https://github.com/stan-dev/cmdstan/releases/download/v2.23.0/colab-cmdstan-2.23.0.tar.gz'
	if not os.path.exists(tgz_file):