
import cPickle
import gzip
import logging
import os
import sys
import tempfile
import urllib

import lmj.tnn

logging.basicConfig(
    stream=sys.stdout,
    format='%(levelname).1s %(asctime)s %(message)s',
    level=logging.INFO)

URL = 'http://www.iro.umontreal.ca/~lisa/deep/data/mnist/mnist.pkl.gz'
DATASET = os.path.join(tempfile.gettempdir(), 'mnist.pkl.gz')

if not os.path.isfile(DATASET):
    logging.info('downloading mnist digit dataset from %s' % URL)
    urllib.urlretrieve(URL, DATASET)
    logging.info('saved mnist digits to %s' % DATASET)

class Main(lmj.tnn.Main):
    def get_network(self):
        return lmj.tnn.Classifier

    def get_datasets(self):
        return [(x, y.astype('int32')) for x, y in cPickle.load(gzip.open(DATASET))]

path = os.path.join(tempfile.gettempdir(), 'mnist-classifier.pkl.gz')
Main().train().save(path)
print 'saved network to', path


import cPickle
import gzip
import logging
import os
import sys
import tempfile
import urllib

import lmj.tnn

logging.basicConfig(
    stream=sys.stdout,
    format='%(levelname).1s %(asctime)s %(message)s',
    level=logging.INFO)

URL = 'http://www.iro.umontreal.ca/~lisa/deep/data/mnist/mnist.pkl.gz'
DATASET = os.path.join(tempfile.gettempdir(), 'mnist.pkl.gz')

if not os.path.isfile(DATASET):
    logging.info('downloading mnist digit dataset from %s' % URL)
    urllib.urlretrieve(URL, DATASET)
    logging.info('saved mnist digits to %s' % DATASET)

class Main(lmj.tnn.Main):
    def get_network(self):
        return lmj.tnn.Classifier

    def get_datasets(self):
        return [(x, y.astype('int32')) for x, y in cPickle.load(gzip.open(DATASET))]

m = Main()
path = os.path.join(tempfile.gettempdir(), 'mnist-classifier-%s.pkl.gz' % m.opts.layers)
if os.path.exists(path):
    m.net.load(path)
m.train()
m.net.save(path)

Save mnist classifier model in a file named with the network topology.
Save mnist classifier model in a file named with the network topology.

  
  import cPickle
  import gzip
  import logging
  import os
  import sys
  import tempfile
  import urllib
  
  import lmj.tnn
  
  logging.basicConfig(
      stream=sys.stdout,
      format='%(levelname).1s %(asctime)s %(message)s',
      level=logging.INFO)
  
  URL = 'http://www.iro.umontreal.ca/~lisa/deep/data/mnist/mnist.pkl.gz'
  DATASET = os.path.join(tempfile.gettempdir(), 'mnist.pkl.gz')
  
  if not os.path.isfile(DATASET):
      logging.info('downloading mnist digit dataset from %s' % URL)
      urllib.urlretrieve(URL, DATASET)
      logging.info('saved mnist digits to %s' % DATASET)
  
  class Main(lmj.tnn.Main):
      def get_network(self):
          return lmj.tnn.Classifier
  
      def get_datasets(self):
          return [(x, y.astype('int32')) for x, y in cPickle.load(gzip.open(DATASET))]
  
+ m = Main()
- path = os.path.join(tempfile.gettempdir(), 'mnist-classifier.pkl.gz')
+ path = os.path.join(tempfile.gettempdir(), 'mnist-classifier-%s.pkl.gz' % m.opts.layers)
- Main().train().save(path)
- print 'saved network to', path
+ if os.path.exists(path):
+     m.net.load(path)
+ m.train()
+ m.net.save(path)
  
Save mnist classifier model in a file named with the network topology.
## Code Before:

import cPickle
import gzip
import logging
import os
import sys
import tempfile
import urllib

import lmj.tnn

logging.basicConfig(
    stream=sys.stdout,
    format='%(levelname).1s %(asctime)s %(message)s',
    level=logging.INFO)

URL = 'http://www.iro.umontreal.ca/~lisa/deep/data/mnist/mnist.pkl.gz'
DATASET = os.path.join(tempfile.gettempdir(), 'mnist.pkl.gz')

if not os.path.isfile(DATASET):
    logging.info('downloading mnist digit dataset from %s' % URL)
    urllib.urlretrieve(URL, DATASET)
    logging.info('saved mnist digits to %s' % DATASET)

class Main(lmj.tnn.Main):
    def get_network(self):
        return lmj.tnn.Classifier

    def get_datasets(self):
        return [(x, y.astype('int32')) for x, y in cPickle.load(gzip.open(DATASET))]

path = os.path.join(tempfile.gettempdir(), 'mnist-classifier.pkl.gz')
Main().train().save(path)
print 'saved network to', path

## Instruction:
Save mnist classifier model in a file named with the network topology.
## Code After:

import cPickle
import gzip
import logging
import os
import sys
import tempfile
import urllib

import lmj.tnn

logging.basicConfig(
    stream=sys.stdout,
    format='%(levelname).1s %(asctime)s %(message)s',
    level=logging.INFO)

URL = 'http://www.iro.umontreal.ca/~lisa/deep/data/mnist/mnist.pkl.gz'
DATASET = os.path.join(tempfile.gettempdir(), 'mnist.pkl.gz')

if not os.path.isfile(DATASET):
    logging.info('downloading mnist digit dataset from %s' % URL)
    urllib.urlretrieve(URL, DATASET)
    logging.info('saved mnist digits to %s' % DATASET)

class Main(lmj.tnn.Main):
    def get_network(self):
        return lmj.tnn.Classifier

    def get_datasets(self):
        return [(x, y.astype('int32')) for x, y in cPickle.load(gzip.open(DATASET))]

m = Main()
path = os.path.join(tempfile.gettempdir(), 'mnist-classifier-%s.pkl.gz' % m.opts.layers)
if os.path.exists(path):
    m.net.load(path)
m.train()
m.net.save(path)
