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### Visualize your network's feature maps here.
### Feel free to use as many code cells as needed.
 
# image_input: the test image being fed into the network to produce the feature maps
# tf_activation: should be a tf variable name used during your training procedure that represents the calculated state of a specific weight layer
# activation_min/max: can be used to view the activation contrast in more detail, by default matplot sets min and max to the actual min and max values of the output
# plt_num: used to plot out multiple different weight feature map sets on the same block, just extend the plt number for each new feature map entry
def outputFeatureMap(image_input, tf_activation, activation_min=-1, activation_max=-1 ,plt_num=1):
    # Here make sure to preprocess your image_input in a way your network expects
    # with size, normalization, ect if needed

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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
Send 1K bytes over 1 Gbps network        10,000   ns    0.01 ms
Read 4K randomly from SSD*              150,000   ns    0.15 ms

zhuangh

Backend Architectures

Twitter

ror, scala, jetty, erlang, thrift, mongrel, comet server, my-sql, memchached, varnish, kestrel(mq), starling, gizzard, cassandra, hadoop, vertica, munin, nagios, awstats

• Scaling Twitter: Making Twitter 10000 Percent Faster
• Scaling Twitter
• Blaine Cook on Scaling Twitter - YouTube

zhuangh

github的多人协作

1. github上你可以用别人的现成的代码 直接 git clone 即可了

2. 然后你也想改代码或者贡献代码咋办？

Fork

zhuangh

var googleapis = require('googleapis')
, OAuth2Client = googleapis.OAuth2Client
, config = require('./config.json');

var oauth2Client = new OAuth2Client(config.CLIENT_ID, config.CLIENT_SECRET, config.REDIRECT_URL);

zhuangh

#ifdef _MSC_VER
#include <boost/config/compiler/visualc.hpp>
#endif
#include <boost/property_tree/ptree.hpp>
#include <boost/property_tree/json_parser.hpp>
#include <boost/foreach.hpp>
#include <cassert>
#include <exception>
#include <iostream>
#include <sstream>

zhuangh

#include <boost/uuid/sha1.hpp>
#include <sstream>
#include <cstddef>
#include <string>

std::string Sha1sum(void *data, std::size_t count) {
  boost::uuids::detail::sha1 hasher;
  char hash[20];
  hasher.process_bytes(data, count);
  unsigned int digest[5];