gdshen

name: "VGG_ILSVRC_16_layers"
layer {
  top: "data"
  type: "ImageData"
  top: "label"
  name: "data"
  transform_param {
    mirror: true
    crop_size: 224
    mean_file: "imagenet_mean.binaryproto"

gdshen

# generate (0,0), (0,1), ... , (0,4), (1,0), (1,1), ... (1, 4), ..., (4,4) pair
np.mgrid[0:5, 0:5].T.reshape(-1, 2)

gdshen

import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.optim as optim

a = torch.ones(1,2)
b = torch.nn.Linear(2,1)
b.zero_grad()

c = b(Variable(a))

gdshen

ssh-keyscan -t rsa github.com >> ~/.ssh/known_hosts

gdshen

ruleSets:
- name: tiny_gfwlist
  rules:
  - instagram, PROXY
  - blogspot, PROXY
  - google, PROXY
  - facebook, PROXY
  - youtube, PROXY
  - twitter, PROXY
  - gmail, PROXY

gdshen

ruleSets:
- name: gfwlist_official
  rules: 
  - IP-CIDR,192.168.0.0/16,DIRECT
  - IP-CIDR,10.0.0.0/8,DIRECT
  - IP-CIDR,172.16.0.0/12,DIRECT
  - IP-CIDR,127.0.0.0/8,DIRECT
  - IP-CIDR,91.108.56.0/22,Proxy
  - IP-CIDR,91.108.4.0/22,Proxy
  - IP-CIDR,109.239.140.0/24,Proxy

gdshen

Movies Recommendation:

• MovieLens - Movie Recommendation Data Sets http://www.grouplens.org/node/73
• Yahoo! - Movie, Music, and Images Ratings Data Sets http://webscope.sandbox.yahoo.com/catalog.php?datatype=r
• Jester - Movie Ratings Data Sets (Collaborative Filtering Dataset) http://www.ieor.berkeley.edu/~goldberg/jester-data/
• Cornell University - Movie-review data for use in sentiment-analysis experiments http://www.cs.cornell.edu/people/pabo/movie-review-data/

Music Recommendation:

• Last.fm - Music Recommendation Data Sets http://www.dtic.upf.edu/~ocelma/MusicRecommendationDataset/index.html

gdshen

def new_count(n):
    def f():
        nonlocal n
        n += 1
        return n
    return f