added metric AccuracyWithIgnoreLabel

src/main/resources/templates/gluon/CNNSupervisedTrainer.ftl

@@ -87,6 +87,33 @@ class DiceLoss(gluon.loss.Loss):
         diceloss = self.dice_loss(F, pred, label)
         return F.mean(loss, axis=self._batch_axis, exclude=True) + diceloss
 
+@mx.metric.register
+class ACCURACY_IGNORE_LABEL(mx.metric.EvalMetric):
+    def __init__(self, axis=1, ignore_label=255, name='accuracy',
+                 output_names=None, label_names=None):
+        super(ACCURACY_IGNORE_LABEL, self).__init__(
+            name, axis=axis,
+            output_names=output_names, label_names=label_names)
+        self.axis = axis
+        self.ignore_label = ignore_label
+
+    def update(self, labels, preds):
+        mx.metric.check_label_shapes(labels, preds)
+
+        for label, pred_label in zip(labels, preds):
+            if pred_label.shape != label.shape:
+                pred_label = mx.nd.argmax(pred_label, axis=self.axis, keepdims=True)
+            label = label.astype('int32')
+            pred_label = pred_label.astype('int32').as_in_context(label.context)
+
+            mx.metric.check_label_shapes(label, pred_label)
+
+            correct = mx.nd.sum( (label == pred_label) * (label != self.ignore_label) ).asscalar()
+            total = mx.nd.sum( (label != self.ignore_label) ).asscalar()
+
+            self.sum_metric += correct
+            self.num_inst += total
+
 @mx.metric.register
 class BLEU(mx.metric.EvalMetric):
     N = 4

src/main/resources/templates/gluon/CNNTrainer.ftl

@@ -66,6 +66,12 @@ if __name__ == "__main__":
         eval_metric_params={
 <#if (config.evalMetric.exclude)??>
             'exclude': [<#list config.evalMetric.exclude as value>${value}<#sep>, </#list>],
+</#if>
+<#if (config.evalMetric.exclude)??>
+            'axis': ${config.evalMetric.axis},
+</#if>
+<#if (config.evalMetric.exclude)??>
+            'ignore_label': ${config.evalMetric.ignore_label},
 </#if>
         },
 </#if>

src/main/resources/templates/gluon/gan/Trainer.ftl

@@ -65,7 +65,10 @@ if __name__ == "__main__":
         preprocessing=${config.preprocessor?string("True","False")},
 </#if>
 <#if (config.evalMetric)??>
-        eval_metric='${config.evalMetric}',
+        eval_metric='${config.evalMetric.name}',
+        eval_metric_params={
+<#if (config.evalMetric.exclude)??>
+            'exclude': [<#list config.evalMetric.exclude as value>${value}<#sep>, </#list>],
 </#if>
 <#if (config.configuration.optimizer)??>
         optimizer='${config.optimizerName}',