[Doc] Fix Typo

docs/source/concepts/configuring.rst

@@ -104,7 +104,7 @@ You can change it like so:
 
 .. code-block:: console
 
-   python benchmarl/run.py task=vmas/balance algorithm=mappo model=layers/mlp model=layers/mlp model.layer_class="torch.nn.Linear" "model.num_cells=[32,32]" model.activation_class="torch.nn.ReLU"
+   python benchmarl/run.py task=vmas/balance algorithm=mappo model=layers/mlp model.layer_class="torch.nn.Linear" "model.num_cells=[32,32]" model.activation_class="torch.nn.ReLU"
 
 
 Available models and their configs can be found at `benchmarl/conf/model/layers <https://github.com/facebookresearch/BenchMARL/blob/main/benchmarl/conf/model/layers>`__.

examples/extending/model/custom_model.py

@@ -21,7 +21,7 @@ class CustomModel(Model):
     def __init__(
         self,
         custom_param: int,
-        activation_function: Type[nn.Module],
+        activation_class: Type[nn.Module],
         **kwargs,
     ):
         # Models in BenchMARL are instantiated per agent group.
@@ -34,7 +34,7 @@ def __init__(
 
         # You can create your custom attributes
         self.custom_param = custom_param
-        self.activation_function = activation_function
+        self.activation_function = activation_class
 
         # And access some of the ones already available to your module
         _ = self.input_spec  # Like its input_spec
@@ -166,7 +166,7 @@ def _forward(self, tensordict: TensorDictBase) -> TensorDictBase:
 class CustomModelConfig(ModelConfig):
     # The config parameters for this class, these will be loaded from yaml
     custom_param: int = MISSING
-    activation_function: Type[nn.Module] = MISSING
+    activation_class: Type[nn.Module] = MISSING
 
     @staticmethod
     def associated_class():

examples/extending/model/custommodel.yaml

@@ -1,4 +1,4 @@
 
 name: custom_model
 custom_param: 3
-activation_function: torch.nn.Tanh
+activation_class: torch.nn.Tanh