rahul003

h1. Sublime Text 2 - Useful Shortcuts (PC)

Loosely ordered with the commands I use most towards the top. Sublime also offer "full documentation":http://www.sublimetext.com/docs/2/.

h2. Editing

| *Ctrl+C* | copy current line (if no selection) |
| *Ctrl+X* | cut current line (if no selection) |
| *Ctrl+⇧+K*| delete line |
| *Ctrl+↩* | insert line after |

rahul003

# Adding tasks:
# m h dom mon dow command


59 23 * * 1,2,3,4,5,6 /home/rh/git/useful_scripts/backup/incr_backup.sh
59 23 * * 7 /home/rh/git/useful_scripts/backup/full_backup.sh

#view cron tasks

crontab -l

rahul003

import networkx as nx
import matplotlib.pyplot as plt
import pylab
import csv
from random import random
G=nx.Graph()

with open('ai3.csv', 'rb') as csvfile:
	spamreader = csv.reader(csvfile, delimiter=',')
	for row in spamreader:

rahul003

sudo apt-get install -y ninja-build ccache

# ccache for better cached compilers
echo 'export PATH="/usr/lib/ccache:$PATH"' | tee -a ~/.bashrc
source ~/.bashrc
ccache -F 0
ccache -M 0

# OPTIONAL
# llvm-lit for omp build

rahul003

# install protobuf 25
brew install wget
wget https://raw.githubusercontent.com/mli/deps/master/build/protobuf-2.5.0.tar.gz
tar -xvf protobuf-2.5.0.tar.gz
cd protobuf-2.5.0
export CFLAGS=-fPIC
export CXXFLAGS=-fPIC
./configure
make -j 4
make install

rahul003

sudo apt-get install -y linux-headers-$(uname -r)
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.1.85-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1604_9.1.85-1_amd64.deb
sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
sudo dpkg -i cuda-repo-ubuntu1604_9.1.85-1_amd64.deb
sudo apt-get update
sudo apt-get install -y cuda
/usr/bin/nvidia-persistenced --verbose
sudo apt-get install -y g++ freeglut3-dev build-essential libx11-dev     libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev
wget http://developer2.download.nvidia.com/compute/machine-learning/cudnn/secure/v7.0.5/prod/9.0_20171129/Ubuntu16_04-x64/libcudnn7_7.0.5.15-1%2Bcuda9.0_amd64.deb?B6oKBFMYCPOY-7IYUsEd5RXHqo4X7I6Y7Ocbi0HI3sKsDx58Lyrsw921spJrwCNsOaLkJuMGkGsNLqGX6FJRAa0qXMfv5E38ZVCRdEspFRIcz7tYXUm6SGdsC-w4Vm5sxwoxmk1a7j0hNVKnj5uMF7ZMrt80tiOM9MdfjvtSV-RRNdFGmavFjX7pqGvpTcFHFwxdYCYZtvzOvD6t10hltLcrA7tJXRdwkQQGaid2W-yjnx7e4lI

rahul003

#include <iostream>
#include <chrono>

class Timer {
public:
    Timer() : beg_(clock_::now()) {}
    void reset() { beg_ = clock_::now(); }
    double elapsed() const { 
        return std::chrono::duration_cast<second_>
            (clock_::now() - beg_).count(); }

rahul003

#pragma once

#include <memory>

#include <ATen/ATen.h>
#include <c10d/ProcessGroup.hpp>
#include <torch/csrc/utils/pybind.h>

namespace c10d {

rahul003

nvidia-smi -q >> /tmp/nvidia-smi.out && grep "Remapping Failure Occurred" /tmp/nvidia-smi.out | grep "Yes" && hostname

rahul003

# pyright: basic, reportMissingImports=false
# Container-only build tool (tensorrt/torch/onnx are present only inside the
# TRT build image, not bazel deps); strict typing buys nothing here.
"""Build a multi-profile TensorRT plan engine for an encoder cross-encoder
reranker (Ettin 68m/400m today; historically the Nemotron 500m).

Takes an already-exported ONNX and compiles a serialized TRT engine for
the local GPU/TRT version — engines are not portable across either, so we
always build on the target box (GH200/aarch64). The ONNX source is either:
  - `source.onnx` from `export_hf_to_onnx.py` (the Ettin chain — the path