[Fix] Fix eval (#931)

* update develop mkdocs

* allow alias for mike

* fix and refine eval.py

* fix

Author: HydrogenSulfate

ppsci/solver/eval.py

@@ -167,6 +167,10 @@ def _eval_by_dataset(
         for metric_name, metric_func in _validator.metric.items():
             # NOTE: compute metric with entire output and label
             metric_dict = metric_func(all_output, all_label)
+            assert metric_name not in metric_dict_group, (
+                f"Metric name({metric_name}) already exists, please ensure all metric "
+                "names are unique over all validators."
+            )
             metric_dict_group[metric_name] = {
                 k: float(v) for k, v in metric_dict.items()
             }
@@ -215,7 +219,6 @@ def _eval_by_batch(
         num_samples = _get_dataset_length(_validator.data_loader)
 
         loss_dict = misc.Prettydefaultdict(float)
-        metric_dict_group: Dict[str, Dict[str, float]] = misc.PrettyOrderedDict()
         reader_tic = time.perf_counter()
         batch_tic = time.perf_counter()
         for iter_id, batch in enumerate(_validator.data_loader, start=1):
@@ -251,9 +254,12 @@ def _eval_by_batch(
 
             # collect batch metric
             for metric_name, metric_func in _validator.metric.items():
+                assert metric_name not in metric_dict_group, (
+                    f"Metric name({metric_name}) already exists, please ensure all metric "
+                    "names are unique over all validators."
+                )
+                metric_dict_group[metric_name] = misc.Prettydefaultdict(list)
                 metric_dict = metric_func(output_dict, label_dict)
-                if metric_name not in metric_dict_group:
-                    metric_dict_group[metric_name] = misc.Prettydefaultdict(list)
                 for var_name, metric_value in metric_dict.items():
                     metric_dict_group[metric_name][var_name].append(
                         metric_value
@@ -284,9 +290,9 @@ def _eval_by_batch(
         # concatenate all metric and discard metric of padded sample(s)
         for metric_name, metric_dict in metric_dict_group.items():
             for var_name, metric_value in metric_dict.items():
-                # NOTE: concat all metric(scalars) into metric vector
+                # NOTE: concat single metric(scalar) list into metric vector
                 metric_value = paddle.concat(metric_value)[:num_samples]
-                # NOTE: compute metric via averaging metric vector,
+                # NOTE: compute metric via averaging metric over all samples,
                 # this might be not general for certain evaluation case
                 metric_value = float(metric_value.mean())
                 metric_dict_group[metric_name][var_name] = metric_value