Tests: refactor cleanup (#1744)

* wip

* cleaning

* optim imports

* -

* default hparams

* fix restore

* fix imports

tests/base/model_utilities.py

@@ -0,0 +1,28 @@
+from torch.utils.data import DataLoader
+
+from tests.base.datasets import TrialMNIST
+
+
+class ModelTemplateData:
+    hparams: ...
+
+    def dataloader(self, train):
+        dataset = TrialMNIST(root=self.hparams.data_root, train=train, download=True)
+
+        loader = DataLoader(
+            dataset=dataset,
+            batch_size=self.hparams.batch_size,
+            # test and valid shall not be shuffled
+            shuffle=train,
+        )
+        return loader
+
+
+class ModelTemplateUtils:
+
+    def get_output_metric(self, output, name):
+        if isinstance(output, dict):
+            val = output[name]
+        else:  # if it is 2level deep -> per dataloader and per batch
+            val = sum(out[name] for out in output) / len(output)
+        return val