Allow metrics 'crossentropy', 'ce' (keras-team#8864)

* Allow metrics 'crossentropy', 'ce' * append correct suffix
satels · Jan 12, 2018 · 76c5b61 · 76c5b61
1 parent 616a9b0
commit 76c5b61
Showing 1 changed file with 22 additions and 9 deletions.
diff --git a/keras/engine/training.py b/keras/engine/training.py
@@ -871,22 +871,35 @@ def handle_metrics(metrics, weights=None):
                     metric_name_prefix = 'weighted_' if weights is not None else ''
 
                     for metric in metrics:
-                        if metric == 'accuracy' or metric == 'acc':
-                            # custom handling of accuracy
+                        if metric in ('accuracy', 'acc', 'crossentropy', 'ce'):
+                            # custom handling of accuracy/crossentropy
                             # (because of class mode duality)
                             output_shape = self._internal_output_shapes[i]
                             if (output_shape[-1] == 1 or
                                self.loss_functions[i] == losses.binary_crossentropy):
-                                # case: binary accuracy
-                                acc_fn = metrics_module.binary_accuracy
+                                # case: binary accuracy/crossentropy
+                                if metric in ('accuracy', 'acc'):
+                                    acc_fn = metrics_module.binary_accuracy
+                                elif metric in ('crossentropy', 'ce'):
+                                    acc_fn = metrics_module.binary_crossentropy
                             elif self.loss_functions[i] == losses.sparse_categorical_crossentropy:
-                                # case: categorical accuracy with sparse targets
-                                acc_fn = metrics_module.sparse_categorical_accuracy
+                                # case: categorical accuracy/crossentropy with sparse targets
+                                if metric in ('accuracy', 'acc'):
+                                    acc_fn = metrics_module.sparse_categorical_accuracy
+                                elif metric in ('crossentropy', 'ce'):
+                                    acc_fn = metrics_module.sparse_categorical_crossentropy
                             else:
-                                acc_fn = metrics_module.categorical_accuracy
-
+                                # case: categorical accuracy/crossentropy
+                                if metric in ('accuracy', 'acc'):
+                                    acc_fn = metrics_module.categorical_accuracy
+                                elif metric in ('crossentropy', 'ce'):
+                                    acc_fn = metrics_module.categorical_crossentropy
+                            if metric in ('accuracy', 'acc'):
+                                    suffix = 'acc'
+                            elif metric in ('crossentropy', 'ce'):
+                                    suffix = 'ce'
                             weighted_metric_fn = _weighted_masked_objective(acc_fn)
-                            metric_name = metric_name_prefix + 'acc'
+                            metric_name = metric_name_prefix + suffix
                         else:
                             metric_fn = metrics_module.get(metric)
                             weighted_metric_fn = _weighted_masked_objective(metric_fn)