soroushmehr

// Tested on Chrome (December 2020) and macOS Catalina
// Install "Run Javascript" Chrome extension
// Go to nips.cc e.g. https://nips.cc/Conferences/2020/Schedule
// Change the `year` variable accordingly
// Select "Run Javascript" icon from top-right
// Paste the following script into it, select "Save & Run" and "Enable on nips.cc"
// In Chrome settings for nips.cc change the pop-up behavior to "Allow"
// Now everytime you visit NeurIPS schedules and a list of "cards,"
// you will see "[open tab!]" next to them that you can select "Open link in new tab"
// from right-click menu

soroushmehr

import gym
from IPython import display
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline

env = gym.make('Breakout-v0')
env.reset()
img = plt.imshow(env.render(mode='rgb_array')) # only call this once
for _ in range(100):

soroushmehr

'''
See: https://github.com/pytorch/pytorch/issues/2013
Q: Will view preserve the spatial orientation as in the original tensor?

Run: python -u test_view_5d.py
'''

import random
import numpy as np
import torch

soroushmehr

import torch
import torch.nn as nn
from torch.nn import functional as F
from torch.autograd import Variable
from torch import optim
import numpy as np
import math, random

# Generating a noisy multi-sin wave 

soroushmehr

"""
Install CoreNLP

Setup a server:
$ cd /home/somehri/corenlp/stanford-corenlp-full-2017-06-09
$ java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer

Install PyCoreNLP:
https://github.com/smilli/py-corenlp

soroushmehr

import types
import tensorflow as tf 
import numpy as np

# Expressions are represented as lists of lists,
# in lisp style -- the symbol name is the head (first element)
# of the list, and the arguments follow.

# add an expression to an expression list, recursively if necessary.
def add_expr_to_list(exprlist, expr):

soroushmehr

soroushmehr

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

soroushmehr

Latency Comparison Numbers
--------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

soroushmehr

# Author: Kyle Kastner
# License: BSD 3-Clause
import torch as th
import torch.nn as nn
import torch.optim as optim
from torch.autograd import Variable
import torch.nn.functional as F
from torch.utils.data import TensorDataset, DataLoader
import time
import numpy as np