replace Hparams by init args

tests/base/model_template.py

@@ -65,7 +65,8 @@ def __init__(self,
         self.b2 = b2
 
         # if you specify an example input, the summary will show input/output for each layer
-        self.example_input_array = torch.rand(5, 28 * 28)
+        # TODO: to be fixed in #1773
+        #self.example_input_array = torch.rand(5, 28 * 28)
 
         # build model
         self.__build_model()

tests/models/test_hparams.py

@@ -9,6 +9,7 @@
 
 
 class SubClassEvalModel(EvalModelTemplate):
+    any_other_loss = torch.nn.CrossEntropyLoss()
 
     def __init__(self, *args, subclass_arg=1200, **kwargs):
         super().__init__(*args, **kwargs)
@@ -56,13 +57,13 @@ def test_collect_init_arguments(tmpdir, cls):
     assert CHECKPOINT_KEY_MODULE_ARGS in raw_checkpoint
     assert raw_checkpoint[CHECKPOINT_KEY_MODULE_ARGS]['batch_size'] == 179
 
-    if isinstance(model, AggSubClassEvalModel):
-        assert isinstance(model.my_loss, torch.nn.CrossEntropyLoss)
-
     # verify that model loads correctly
     model = cls.load_from_checkpoint(raw_checkpoint_path)
     assert model.batch_size == 179
 
+    if isinstance(model, AggSubClassEvalModel):
+        assert isinstance(model.my_loss, torch.nn.CrossEntropyLoss)
+
     # verify that we can overwrite whatever we want
     model = cls.load_from_checkpoint(raw_checkpoint_path, batch_size=99)
     assert model.batch_size == 99