Train with synthetic documents

Closes #11 (closed)

dan/manager/metrics.py

@@ -127,7 +127,13 @@ class MetricManager:
                 )
                 if output:
                     display_values["nb_words"] = np.sum(self.epoch_metrics["nb_words"])
-            elif metric_name in ["loss", "loss_ctc", "loss_ce", "syn_max_lines"]:
+            elif metric_name in [
+                "loss",
+                "loss_ctc",
+                "loss_ce",
+                "syn_max_lines",
+                "syn_prob_lines",
+            ]:
                 value = np.average(
                     self.epoch_metrics[metric_name],
                     weights=np.array(self.epoch_metrics["nb_samples"]),
@@ -182,6 +188,7 @@ class MetricManager:
                 "loss_ce",
                 "loss",
                 "syn_max_lines",
+                "syn_prob_lines",
             ]:
                 metrics[metric_name] = [
                     values[metric_name],