jhowliu jhowliu

## HW2_Sol.tex
\documentclass[12pt]{article}
\usepackage{amsmath}
\title{Numerical Analysis Homework 2 Solution}
\begin{document}

\begin{enumerate}
    \item
        \begin{enumerate}
            \item Find $f(0.43)$
            \begin{enumerate}

## .git-completion.bash
# bash/zsh completion support for core Git.
#
# Copyright (C) 2006,2007 Shawn O. Pearce <spearce@spearce.org>
# Conceptually based on gitcompletion (http://gitweb.hawaga.org.uk/).
# Distributed under the GNU General Public License, version 2.0.
#
# The contained completion routines provide support for completing:
#
#    *) local and remote branch names
#    *) local and remote tag names

## .DS_Store

      
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## Serial
import serial

if __name__ == '__main__':
    ser = serial.Serial(SerialPort, Baud)

    line = ser.readline()

    while line
        line = ser.readline()

## Han.csv

          
            44
            -16408
            904
            -48
            -102
            100
            1360791

            
              -8
              -16408
              832
              -43
              -125
              113
              1360865

            
              0
              -16372
              844
              -35
              -113
              110
              1360936

            
              168
              -16364
              780
              -15
              -119
              67
              1361008

            
              104
              -16356
              696
              -35
              -152
              90
              1361082

            
              12
              -16444
              852
              -27
              -101
              122
              1361156

            
              132
              -16464
              772
              -23
              -122
              124
              1361227

            
              60
              -16420
              884
              -54
              -130
              90
              1361301

            
              40
              -16420
              872
              -45
              -133
              129
              1361373

            
              28
              -16396
              668
              -9
              -99
              68
              1361446

## tess
ss

## client.c
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <sys/types.h>
#include <sys/socket.h>
#include <netinet/in.h>
#include <arpa/inet.h>

#define BUFFER_SIZE 512
#define SERVER_PORT 3000

## .sh
echo 'Bob brought the pizza to Alice.' | syntaxnet/demo.sh

2017-04-19 16:47:21.770904: W external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2017-04-19 16:47:21.770922: W external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-04-19 16:47:21.770928: W external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-04-19 16:47:21.770930: W external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could spee

## .profile
  # cuda path
  export LD_LIBRARY_PATH="/usr/local/cuda-8.0/lib64:/usr/local/cuda-8.0/extras/CUPTI/lib64:$LD_LIBRARY_PATH"
  export CUDA_HOME="/usr/local/cuda-8.0"
  export PATH="$PATH:$CUDA_HOME/bin"
  export CUDNN_HOME=${CUDA_HOME}
  export TF_NEED_CUDA=1
  export CUDA_TOOLKIT_PATH=$CUDA_HOME
  export TF_CUDA_VERSION=8.0
  export TF_CUDNN_VERSION=5
  export CUDNN_INSTALL_PATH=$CUDA_HOME

## app.py
from flask import render_template, request, redirect
from app.model import get_result_with_text
from app import app


conversations = []

@app.route('/')
@app.route('/index')
def home():
	\documentclass[12pt]{article}
	\usepackage{amsmath}
	\title{Numerical Analysis Homework 2 Solution}
	\begin{document}

	\begin{enumerate}
	\item
	\begin{enumerate}
	\item Find $f(0.43)$
	\begin{enumerate}
	# bash/zsh completion support for core Git.
	#
	# Copyright (C) 2006,2007 Shawn O. Pearce <spearce@spearce.org>
	# Conceptually based on gitcompletion (http://gitweb.hawaga.org.uk/).
	# Distributed under the GNU General Public License, version 2.0.
	#
	# The contained completion routines provide support for completing:
	#
	# *) local and remote branch names
	# *) local and remote tag names
	import serial

	if __name__ == '__main__':
	ser = serial.Serial(SerialPort, Baud)

	line = ser.readline()

	while line
	line = ser.readline()
44	-16408	904	-48	-102	100	1360791
-8	-16408	832	-43	-125	113	1360865
0	-16372	844	-35	-113	110	1360936
168	-16364	780	-15	-119	67	1361008
104	-16356	696	-35	-152	90	1361082
12	-16444	852	-27	-101	122	1361156
132	-16464	772	-23	-122	124	1361227
60	-16420	884	-54	-130	90	1361301
40	-16420	872	-45	-133	129	1361373
28	-16396	668	-9	-99	68	1361446
	#include <stdio.h>
	#include <stdlib.h>
	#include <string.h>
	#include <sys/types.h>
	#include <sys/socket.h>
	#include <netinet/in.h>
	#include <arpa/inet.h>

	#define BUFFER_SIZE 512
	#define SERVER_PORT 3000
	echo 'Bob brought the pizza to Alice.' \| syntaxnet/demo.sh

	2017-04-19 16:47:21.770904: W external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
	2017-04-19 16:47:21.770922: W external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
	2017-04-19 16:47:21.770928: W external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
	2017-04-19 16:47:21.770930: W external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could spee
	# cuda path
	export LD_LIBRARY_PATH="/usr/local/cuda-8.0/lib64:/usr/local/cuda-8.0/extras/CUPTI/lib64:$LD_LIBRARY_PATH"
	export CUDA_HOME="/usr/local/cuda-8.0"
	export PATH="$PATH:$CUDA_HOME/bin"
	export CUDNN_HOME=${CUDA_HOME}
	export TF_NEED_CUDA=1
	export CUDA_TOOLKIT_PATH=$CUDA_HOME
	export TF_CUDA_VERSION=8.0
	export TF_CUDNN_VERSION=5
	export CUDNN_INSTALL_PATH=$CUDA_HOME
	from flask import render_template, request, redirect
	from app.model import get_result_with_text
	from app import app


	conversations = []

	@app.route('/')
	@app.route('/index')
	def home():