Python3 division.

multi_categorical_gans/datasets/dataset.py

@@ -1,3 +1,5 @@
+from __future__ import division
+
 import numpy as np
 
 
@@ -29,7 +31,7 @@ def __init__(self, features, indices, batch_size):
         self.batch_size = batch_size
 
         self.batch_index = 0
-        self.num_batches = int(np.ceil(len(features) / float(batch_size)))
+        self.num_batches = int(np.ceil(len(features) / batch_size))
 
     def __iter__(self):
         return self

multi_categorical_gans/datasets/synthetic/generate.py

@@ -1,3 +1,4 @@
+from __future__ import division
 from __future__ import print_function
 
 import argparse
@@ -53,7 +54,7 @@ def print_matrix_stats(matrix, num_samples, num_features):
     print("Mean ones per column:", num_ones_per_column.mean())
     print("Total ones:", num_ones)
     print("Total positions:", num_positions)
-    print("Total ratio of ones:", num_ones / float(num_positions))
+    print("Total ratio of ones:", num_ones / num_positions)
     print("Empty rows:", np.sum(num_ones_per_row == 0))
     print("Full rows:", np.sum(num_ones_per_row == num_features))
     print("Empty columns:", np.sum(num_ones_per_column == 0))

multi_categorical_gans/methods/mc_gumbel/trainer.py

@@ -1,3 +1,4 @@
+from __future__ import division
 from __future__ import print_function
 
 import argparse

multi_categorical_gans/methods/medgan/trainer.py

@@ -1,3 +1,4 @@
+from __future__ import division
 from __future__ import print_function
 
 import argparse

multi_categorical_gans/metrics/mse_probabilities_by_dimension.py

@@ -1,3 +1,4 @@
+from __future__ import division
 from __future__ import print_function
 
 import argparse
@@ -10,7 +11,7 @@
 
 
 def probability(data):
-    return data.sum() / float(data.shape[0])
+    return data.sum() / data.shape[0]
 
 
 def probabilities_by_dimension(data):