Kim's sentence classification model: Upgrade to Python 3 (#36)

Kim's sentence classification model: Upgrade to Python 3, per issue #31

kim_cnn/configurable.py

@@ -8,7 +8,7 @@ from __future__ import print_function
 import os
 import argparse
 
-from ConfigParser import SafeConfigParser
+from configparser import SafeConfigParser
 
 
 class Configurable(object):
@@ -37,7 +37,7 @@ class Configurable(object):
     config_file = kwargs.pop("config_file", "")
     config.read(config_file)
     # Override the config setting if the (k,v) specified in command line
-    for option, value in kwargs.iteritems():
+    for option, value in kwargs.items():
       assigned = False
       for section in config.sections():
         if option in config.options(section):

kim_cnn/dataset.py

@@ -21,7 +21,7 @@ class Dataset(Configurable):
     super(Dataset, self).__init__(*args, **kwargs)
     self._train = (filename == self.train_file)
     self.vocabs = vocabs
-    self.buckets = [Bucket(self._config, name='Sents-%d' % i) for i in xrange(self.n_bkts)]
+    self.buckets = [Bucket(self._config, name='Sents-%d' % i) for i in range(self.n_bkts)]
     self.id2position = []
     self.len2bkts = {}
     self.vocabs = vocabs

kim_cnn/etc/__init__.py

@@ -1,2 +1,2 @@
-from kmeans import KMeans
-from utils import clean_str, clean_str_sst
+from etc.kmeans import KMeans
+from etc.utils import clean_str, clean_str_sst

kim_cnn/etc/kmeans.py

@@ -86,7 +86,7 @@ class KMeans(object):
   def recenter(self):
     """"""
 
-    for split_idx in xrange(len(self._splits)):
+    for split_idx in range(len(self._splits)):
       split = self._splits[split_idx]
       len_idx = self._split2len_idx[split]
       if split == self._splits[-1]:
@@ -173,7 +173,7 @@ if __name__ == '__main__':
   """"""
 
   len_cntr = Counter()
-  for i in xrange(10000):
+  for i in range(10000):
     len_cntr[1 + int(10 ** (1 + np.random.randn()))] += 1
   print(len_cntr)
   kmeans = KMeans(10, len_cntr)

kim_cnn/main.py

@@ -26,7 +26,7 @@ if __name__=='__main__':
   args, extra_args = argparser.parse_known_args()
   # args.train = True/False ...
   # extra_args['--some': "xxxx"]
-  cargs = {k: v for (k, v) in vars(Configurable.argparser.parse_args(extra_args)).iteritems() if v is not None}
+  cargs = {k: v for (k, v) in vars(Configurable.argparser.parse_args(extra_args)).items() if v is not None}
 
   if 'model_type' not in cargs:
     print("You need to specify the model_type")

kim_cnn/model/__init__.py

@@ -1 +1 @@
-from cnnText import *
+from model.cnnText import *

kim_cnn/model/cnnText/__init__.py

@@ -1 +1 @@
-from cnntext import CNNText
+from model.cnnText.cnntext import CNNText

kim_cnn/model/cnnText/cnntext.py

@@ -6,7 +6,6 @@ import torch.nn as nn
 
 import torch.nn.functional as F
 
-from configurable import Configurable
 
 class CNNText(nn.Module):
   """

kim_cnn/network/__init__.py

@@ -1 +1 @@
-from cnnTextNetwork import cnnTextNetwork
+from network.cnnTextNetwork import cnnTextNetwork

kim_cnn/vocab.py

@@ -148,7 +148,7 @@ class Vocab(Configurable):
 
 
   def __getitem__(self, key):
-    if isinstance(key, basestring):
+    if isinstance(key, str):
       # Convert the lower case
       if self.lower_case:
         key = key.lower()