Use last (incomplete) minibatch (keras-team#8310)

besport · Oct 31, 2017 · d368dc8 · d368dc8
1 parent 7d63ae6
commit d368dc8
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Showing 2 changed files with 3 additions and 3 deletions.
diff --git a/examples/cifar10_cnn.py b/examples/cifar10_cnn.py
@@ -14,7 +14,7 @@
 from keras.models import Sequential
 from keras.layers import Dense, Dropout, Activation, Flatten
 from keras.layers import Conv2D, MaxPooling2D
-
+import numpy as np
 import os
 
 batch_size = 32
@@ -100,7 +100,7 @@
     # Fit the model on the batches generated by datagen.flow().
     model.fit_generator(datagen.flow(x_train, y_train,
                                      batch_size=batch_size),
-                        steps_per_epoch=x_train.shape[0] // batch_size,
+                        steps_per_epoch=int(np.ceil(x_train.shape[0] / float(batch_size))),
                         epochs=epochs,
                         validation_data=(x_test, y_test),
                         workers=4)

diff --git a/examples/cifar10_resnet.py b/examples/cifar10_resnet.py
@@ -181,7 +181,7 @@
 
     # Fit the model on the batches generated by datagen.flow().
     model.fit_generator(datagen.flow(x_train, y_train, batch_size=batch_size),
-                        steps_per_epoch=x_train.shape[0] // batch_size,
+                        steps_per_epoch=int(np.ceil(x_train.shape[0] / float(batch_size))),
                         validation_data=(x_test, y_test),
                         epochs=epochs, verbose=1, workers=4,
                         callbacks=callbacks)