Remove support for Python 2. Misc fixes.

.travis.yml

@@ -2,7 +2,6 @@ os:
   - linux
 language: python
 python:
-  - 2.7
   - 3.6
 cache: bundler
 install:

1_linear_regression.py

@@ -10,6 +10,7 @@ def build_model():
 
 
 def train(model, loss, optimizer, x, y):
+    model.train()
     x = Variable(x, requires_grad=False)
     y = Variable(y, requires_grad=False)
 

2_logistic_regression.py

@@ -17,6 +17,7 @@ def build_model(input_dim, output_dim):
 
 
 def train(model, loss, optimizer, x_val, y_val):
+    model.train()
     x = Variable(x_val, requires_grad=False)
     y = Variable(y_val, requires_grad=False)
 
@@ -37,6 +38,7 @@ def train(model, loss, optimizer, x_val, y_val):
 
 
 def predict(model, x_val):
+    model.eval()
     x = Variable(x_val, requires_grad=False)
     output = model.forward(x)
     return output.data.numpy().argmax(axis=1)

3_neural_net.py

@@ -16,6 +16,7 @@ def build_model(input_dim, output_dim):
 
 
 def train(model, loss, optimizer, x_val, y_val):
+    model.train()
     x = Variable(x_val, requires_grad=False)
     y = Variable(y_val, requires_grad=False)
 
@@ -36,6 +37,7 @@ def train(model, loss, optimizer, x_val, y_val):
 
 
 def predict(model, x_val):
+    model.eval()
     x = Variable(x_val, requires_grad=False)
     output = model.forward(x)
     return output.data.numpy().argmax(axis=1)

4_modern_neural_net.py

@@ -20,6 +20,7 @@ def build_model(input_dim, output_dim):
 
 
 def train(model, loss, optimizer, x_val, y_val):
+    model.train()
     x = Variable(x_val, requires_grad=False)
     y = Variable(y_val, requires_grad=False)
 
@@ -40,6 +41,7 @@ def train(model, loss, optimizer, x_val, y_val):
 
 
 def predict(model, x_val):
+    model.eval()
     x = Variable(x_val, requires_grad=False)
     output = model.forward(x)
     return output.data.numpy().argmax(axis=1)

5_convolutional_net.py

@@ -34,6 +34,7 @@ def forward(self, x):
 
 
 def train(model, loss, optimizer, x_val, y_val):
+    model.train()
     x = Variable(x_val, requires_grad=False)
     y = Variable(y_val, requires_grad=False)
 
@@ -54,6 +55,7 @@ def train(model, loss, optimizer, x_val, y_val):
 
 
 def predict(model, x_val):
+    model.eval()
     x = Variable(x_val, requires_grad=False)
     output = model.forward(x)
     return output.data.numpy().argmax(axis=1)

6_lstm.py

@@ -1,4 +1,3 @@
-from __future__ import division
 import numpy as np
 
 import torch
@@ -24,6 +23,7 @@ def forward(self, x):
 
 
 def train(model, loss, optimizer, x_val, y_val):
+    model.train()
     x = Variable(x_val, requires_grad=False)
     y = Variable(y_val, requires_grad=False)
 
@@ -44,6 +44,7 @@ def train(model, loss, optimizer, x_val, y_val):
 
 
 def predict(model, x_val):
+    model.eval()
     x = Variable(x_val, requires_grad=False)
     output = model.forward(x)
     return output.data.numpy().argmax(axis=1)

data_util.py

@@ -1,14 +1,9 @@
 import gzip
 import os
+import urllib.request as request
 from os import path
-import numpy as np
-
-import sys
-if sys.version_info.major < 3:
-    import urllib
-else:
-    import urllib.request as request
 
+import numpy as np
 
 DATASET_DIR = 'datasets/'
 
@@ -23,10 +18,7 @@ def download_file(url, local_path):
         os.makedirs(dir_path)
 
     print("Downloading from '%s' ..." % url)
-    if sys.version_info.major < 3:
-        urllib.URLopener().retrieve(url, local_path)
-    else:
-        request.urlretrieve(url, local_path)
+    request.urlretrieve(url, local_path)
 
 
 def download_mnist(local_path):