mlzxy

#!/bin/bash
# Exit on error #
set -e

# Clean up #
rm -rf ~/programs/libevent
rm -rf ~/programs/ncurses
rm -rf ~/programs/tmux

# Variable version #

mlzxy

cmake_minimum_required(VERSION 3.3)
project(opencl_learning)


## Set
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
set(CMAKE_MODULE_PATH "${CMAKE_SOURCE_DIR}")


## Package Find

mlzxy

ROOT=`pwd`
NUMBER_OF_CORES=4


sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive apt-get upgrade -y -q -o Dpkg::Options::="--force-confdef" -o Dpkg::Options::="--force-confold" # If you are OK with all defaults

sudo apt-get install -y libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev
sudo apt-get install -y --no-install-recommends libboost-all-dev
sudo apt-get install -y libatlas-base-dev 

mlzxy

#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>
#include <sys/socket.h>
#include <bluetooth/bluetooth.h>
#include <bluetooth/hci.h>
#include <bluetooth/hci_lib.h>


void query(char* name, char* addr, inquiry_info * ii){

mlzxy

import paho.mqtt.client as mqtt
from gpiozero import LED
from time import sleep
import threading

IP = "192.241.199.185"
PORT = 1883

class Light:
    def __init__(self):

mlzxy

from __future__ import print_function
import numpy as np
np.random.seed(1337)  # for reproducibility
import json
from keras.preprocessing import sequence
from keras.utils import np_utils
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Masking, TimeDistributedDense
from keras.layers.embeddings import Embedding
from keras.layers.recurrent import LSTM

mlzxy

---

自己之前也投过一些简历，参加过career affair, 但并不成功。 身边很多同学都找到了实习，自己却还没着落。

痛定思痛，思考了很多。 这其中诚然有运气成分，但更重要的是太不重视细节，没有把这件事真正放在心上，而忽视细节更是自己性格的致命伤。

mlzxy

module HW where


import Control.Monad.State hiding (when)



tick :: Int -> State String ()
tick _= do
        -- get last intermediate valueP

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inputArg = [['A', 1, 4], ['B', 2, 8], ['C', 1, 5], ['D', 2, 7]]




FINISHED = float('inf')
OVER = -1

mlzxy

# This script installs Caffe and pycaffe on Ubuntu 14.04 x64 or 14.10 x64. CPU only, multi-threaded Caffe.
# Usage: 
# 0. Set up here how many cores you want to use during the installation:
# By default Caffe will use all these cores.
NUMBER_OF_CORES=4
# 1. Execute this script, e.g. "bash compile_caffe_ubuntu_14.04.sh" (~30 to 60 minutes on a new Ubuntu).
# 2. Open a new shell (or run "source ~/.bash_profile"). You're done. You can try 
#    running "import caffe" from the Python interpreter to test.

#http://caffe.berkeleyvision.org/install_apt.html : (general install info: http://caffe.berkeleyvision.org/installation.html)