Rename classes and modules for GNO

pina/model/__init__.py

@@ -10,7 +10,7 @@ __all__ = [
     "AveragingNeuralOperator",
     "LowRankNeuralOperator",
     "Spline",
-    "GNO"
+    "GraphNeuralOperator"
 ]
 
 from .feed_forward import FeedForward, ResidualFeedForward
@@ -21,4 +21,4 @@ from .base_no import KernelNeuralOperator
 from .avno import AveragingNeuralOperator
 from .lno import LowRankNeuralOperator
 from .spline import Spline
-from .gno import GNO
+from .gno import GraphNeuralOperator

pina/model/gno.py

@@ -1,6 +1,6 @@
 import torch
 from torch.nn import Tanh
-from .layers import GraphIntegralLayer
+from .layers import GNOBlock
 from .base_no import KernelNeuralOperator
 
 
@@ -46,7 +46,7 @@ class GraphNeuralKernel(torch.nn.Module):
             internal_func = Tanh
 
         if shared_weights:
-            self.layers = GraphIntegralLayer(
+            self.layers = GNOBlock(
                 width=width,
                 edges_features=edge_features,
                 n_layers=internal_n_layers,
@@ -58,7 +58,7 @@ class GraphNeuralKernel(torch.nn.Module):
             self.forward = self.forward_shared
         else:
             self.layers = torch.nn.ModuleList(
-                [GraphIntegralLayer(
+                [GNOBlock(
                     width=width,
                     edges_features=edge_features,
                     n_layers=internal_n_layers,
@@ -101,7 +101,7 @@ class GraphNeuralKernel(torch.nn.Module):
         return x
 
 
-class GNO(KernelNeuralOperator):
+class GraphNeuralOperator(KernelNeuralOperator):
     """
     TODO add docstring
     """

pina/model/layers/__init__.py

@@ -15,7 +15,7 @@ __all__ = [
     "AVNOBlock",
     "LowRankBlock",
     "RBFBlock",
-    "GraphIntegralLayer"
+    "GNOBlock"
 ]
 
 from .convolution_2d import ContinuousConvBlock
@@ -32,4 +32,4 @@ from .embedding import PeriodicBoundaryEmbedding, FourierFeatureEmbedding
 from .avno_layer import AVNOBlock
 from .lowrank_layer import LowRankBlock
 from .rbf_layer import RBFBlock
-from .graph_integral_kernel import GraphIntegralLayer
+from .gno_block import GNOBlock

pina/model/layers/gno_block.py

@@ -2,10 +2,11 @@ import torch
 from torch_geometric.nn import MessagePassing
 
 
-class GraphIntegralLayer(MessagePassing):
+class GNOBlock(MessagePassing):
     """
     TODO: Add documentation
     """
+
     def __init__(
             self,
             width,
@@ -27,7 +28,7 @@ class GraphIntegralLayer(MessagePassing):
         :type n_layers: int
         """
         from pina.model import FeedForward
-        super(GraphIntegralLayer, self).__init__(aggr='mean')
+        super(GNOBlock, self).__init__(aggr='mean')
         self.width = width
         if layers is None and inner_size is None:
             inner_size = width