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backend.py
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backend.py
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from flask import *
from werkzeug.contrib.profiler import ProfilerMiddleware
from collections import defaultdict
import json
import sys
import cPickle
import os.path
import numpy as np
import veclib
from utils import *
app = Flask(__name__, static_folder='static',
static_url_path='', template_folder='templates')
trained = "/home/ubuntu/data"
fnv = '%s/vectors.fullwiki.1000.s50.num.npy' % trained
fnw = '%s/vectors.fullwiki.1000.s50.words' % trained
ffb = '%s/freebase_types_and_fullwiki.1000.s50.words' % trained
avl = veclib.get_vector_lib(fnv)
#avl = veclib.normalize(avl)
avl = veclib.split(veclib.normalize, avl)
if os.path.exists(fnw + '.pickle'):
aw2i, ai2w = cPickle.load(open(fnw + '.pickle'))
else:
aw2i, ai2w = veclib.get_words(fnw)
cPickle.dump([aw2i, ai2w], open(fnw + '.pickle','w'))
frac = None
if frac:
end = int(avl.shape[0] * frac)
avl = avl[:end]
for i in range(end, avl.shape):
del aw2i[ai2w[i].pop()]
@app.route('/farthest/<raw_query>')
#@json_exception
def farthest(raw_query='{"args":["iphone", "ipad", "ipod", "walkman"]}'):
"""Given a list of arguments, calculate all the N^2 distance matrix
and return the item farthest away. The total distance is just the
distance from a node to all other nodes seperately."""
print 'QUERY'
print raw_query
query = json.loads(raw_query.strip("'"))
nargs = len(query['args'])
words = query['args']
N2, N1, vectors = veclib.build_n2(words, avl, aw2i)
inner, left, right = veclib.common_words(words, vectors, avl, aw2i, ai2w,
N2, N1, blacklist=words)
fb_words = [word.strip() for word in open(ffb).readlines()]
fw2i = {w:i for i, w in enumerate(fb_words)}
fi2w = {i:w for i, w in enumerate(fb_words)}
idx = [aw2i[word] for word in fb_words]
inner_fb, left_fb, right_fb = veclib.common_words(words, vectors, avl[idx], fw2i, fi2w,
N2, N1, blacklist=words, n=1000)
resp = {}
resp['N1'] = [float(x) for x in N1]
resp['args'] = words
resp['inner'] = inner
resp['inner_freebase'] = inner_fb[:50]
resp['left'] = left
resp['left_freebase'] = left_fb[:50]
resp['right'] = right
resp['right_freebase'] = right_fb[:50]
resp['right_word'] = words[N1.argmin()]
text = json.dumps(resp)
return text
@app.route('/nearest/<raw_query>')
@timer
def nearest(raw_query='{"args": [[1.0, "jurassic_park"]]}'):
"""Given the expression, find the appropriate vectors, and evaluate it"""
print 'QUERY'
print raw_query
try:
query = json.loads(raw_query.strip("'"))
total = None
resp = defaultdict(lambda : list)
resp['args'] = query['args']
args_neighbors = []
root_vectors = []
for sign, word in query['args']:
vector = avl[aw2i[word]]
root_vectors.append(vector)
if False:
canon, vectors, sim = veclib.nearest_word(vector, avl, ai2w, n=20)
args_neighbors.append(canon)
else:
args_neighbors.append([None])
if total is None:
total = vector * sign
else:
total += vector * sign
total /= np.sum(total**2.0)
canon, vectors, sim = veclib.nearest_word(total, avl, ai2w, n=20)
root_sims = []
for canonical, vector in zip(canon, vectors):
sims = []
for (sign, word), root_vector in zip(query['args'], root_vectors):
total = (root_vector * vector).astype(np.float128)
#total /= np.sqrt(np.sum(total ** 2.0))
root_sim = np.sum(total,dtype=np.float128)
sims.append(root_sim)
print canonical, word, root_sim
root_sims.append(np.max(sims))
print canonical, max(sims)
resp['result'] = canon
resp['similarity'] = [float(s) for s in sim]
resp['args_neighbors'] = args_neighbors
resp['root_similarity'] = [float(s) for s in root_sims]
send = {}
send.update(resp)
print resp
text = json.dumps(send)
print "RESPONSE"
#print json.dumps(send, sort_keys=True,indent=4, separators=(',', ': '))
except:
print "ERROR"
text = dict(error=str(sys.exc_info()))
text = json.dumps(text)
print text
return text
if __name__ == '__main__':
port = 5005
try:
port = int(sys.argv[-1])
print "Serving port %i" % port
except:
pass
use_flask = False
if use_flask:
app.run(host='0.0.0.0', port=port, debug=True, use_reloader=False)
else:
from twisted.internet import reactor
from twisted.web.server import Site
from twisted.web.wsgi import WSGIResource
resource = WSGIResource(reactor, reactor.getThreadPool(), app)
site = Site(resource)
reactor.listenTCP(port, site, interface="0.0.0.0")
print "Running"
reactor.run()
#app.run(host='0.0.0.0', port=port)