CNN PR [2/4]: Add CNN base class and IceCubeDNN model

src/graphnet/models/cnn/__init__.py

@@ -0,0 +1,4 @@
+"""CNN-specific modules, for performing the main learnable operations."""
+
+from .cnn import CNN
+from .icecube_dnn import IceCubeDNN

src/graphnet/models/cnn/cnn.py

@@ -0,0 +1,35 @@
+"""Base CNN-specific `Model` class(es)."""
+
+from abc import abstractmethod
+
+from torch import Tensor
+from torch_geometric.data import Data
+
+from graphnet.models import Model
+
+
+class CNN(Model):
+    """Base class for all core CNN models in graphnet."""
+
+    def __init__(self, nb_inputs: int, nb_outputs: int) -> None:
+        """Construct `CNN`."""
+        # Base class constructor
+        super().__init__()
+
+        # Member variables
+        self._nb_inputs = nb_inputs
+        self._nb_outputs = nb_outputs
+
+    @property
+    def nb_inputs(self) -> int:
+        """Return number of input features."""
+        return self._nb_inputs
+
+    @property
+    def nb_outputs(self) -> int:
+        """Return number of output features."""
+        return self._nb_outputs
+
+    @abstractmethod
+    def forward(self, data: Data) -> Tensor:
+        """Apply learnable forward pass in model."""