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params = {'backend': 'ps',
          'axes.labelsize': 24, # fontsize for x and y labels (was 10)
          'axes.titlesize': 24,
          'text.fontsize': 24, # was 10
          'legend.fontsize': 24, # was 10
          'xtick.labelsize': 24,
          'ytick.labelsize': 24,
          'text.usetex': True,
          'figure.figsize': [fig_width,fig_height],
          'font.family': 'serif',

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\begin{figure}
\centering
\fbox{
	\begin{minipage}{1in}
		\hfill\vspace{1in}
	\end{minipage}
	}
\caption{Caption}	
\end{figure}

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bsub  -n 1 -R "span[hosts=1]" -R  "rusage[mem=19000,tmp=10000]" -R "select[model==XEON_E5_2670]"  -We 240:00 -J "./mlp_mnist_1_01.sh"

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\DeclareGraphicsExtensions{.png,.pdf}
\graphicspath{{figures/}}

\usepackage{algorithm}
\usepackage{algorithmic}
\usepackage{multirow}
\usepackage{todonotes}
\usepackage{changes}
\definechangesauthor[color=blue]{fr}

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import matplotlib.pyplot as plt

def draw_neural_net(ax, left, right, bottom, top, layer_sizes):
    '''
    Draw a neural network cartoon using matplotilb.
    
    :usage:
        >>> fig = plt.figure(figsize=(12, 12))
        >>> draw_neural_net(fig.gca(), .1, .9, .1, .9, [4, 7, 2])
    

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#Link https://hackernoon.com/a-pip-hack-to-upgrade-all-your-python-packages-492658c49681
sudo pip2 freeze — local | grep -v ‘^\-e’ | cut -d = -f 1 | xargs -n1 sudo pip2 install -U

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#!/usr/bin/python
# -*- coding: utf-8 -*-

import random
import math
import torch
import torch.nn as nn
import torchvision.datasets as dsets
import torchvision.transforms as transforms
import pickle