Merge branch 'master' of skozl.com:e4-gan

1 files changed, 8 insertions, 3 deletions

diff --git a/lenet.py b/lenet.py
index 3ddab06..97479ed 100644
--- a/lenet.py
+++ b/lenet.py
@@ -13,6 +13,8 @@ import random
 from sklearn.metrics import accuracy_score
 from sklearn.model_selection import train_test_split
 
+from classifier_metrics_impl import classifier_score_from_logits
+
 def import_mnist():
   from tensorflow.examples.tutorials.mnist import input_data
   mnist = input_data.read_data_sets("MNIST_data/", reshape=False)
@@ -62,7 +64,8 @@ def get_lenet(shape):
   
   model.add(Dense(units=120, activation='relu'))
   model.add(Dense(units=84, activation='relu'))
-  model.add(Dense(units=10, activation = 'softmax'))
+  #model.add(Dense(units=10, activation = 'softmax'))
+  model.add(Dense(units=10, activation = 'relu'))
   return model
 
 def plot_history(history, metric = None):
@@ -126,10 +129,12 @@ def train_classifier(x_train, y_train, x_val, y_val, batch_size=128, epochs=100,
 def test_classifier(model, x_test, y_true):
   x_test = np.pad(x_test, ((0,0),(2,2),(2,2),(0,0)), 'constant')
   y_pred = model.predict(x_test)
+  logits = tf.convert_to_tensor(y_pred, dtype=tf.float32)
+  inception_score = tf.keras.backend.eval(classifier_score_from_logits(logits))
   y_pred = np.argmax(y_pred, axis=1)
   y_true = np.argmax(y_true, axis=1)
   plot_example_errors(y_pred, y_true, x_test)
-  return accuracy_score(y_true, y_pred)
+  return accuracy_score(y_true, y_pred), inception_score
 
 def mix_data(X_train, y_train, X_validation, y_validation, train_gen, tr_labels_gen, val_gen, val_labels_gen, split=0):
 
@@ -162,4 +167,4 @@ if __name__ == '__main__':
   x_train, y_train, x_val, y_val, x_t, y_t = import_mnist()
   print(y_t.shape)
   model = train_classifier(x_train[:100], y_train[:100], x_val, y_val, epochs=3)
-  test_classifier(model, x_t, y_t)
+  print(test_classifier(model, x_t, y_t))