Dev Update (#582)

* Fix adaptive refinement (#571) --------- Co-authored-by: Dario Coscia <93731561+dario-coscia@users.noreply.github.com> * Remove collector * Fixes * Fixes * rm unnecessary comment * fix advection (#581) * Fix tutorial .html link (#580) * fix problem data collection for v0.1 (#584) * Message Passing Module (#516) * add deep tensor network block * add interaction network block * add radial field network block * add schnet block * add equivariant network block * fix + tests + doc files * fix egnn + equivariance/invariance tests Co-authored-by: Dario Coscia <dariocos99@gmail.com> --------- Co-authored-by: giovanni <giovanni.canali98@yahoo.it> Co-authored-by: AleDinve <giuseppealessio.d@student.unisi.it> * add type checker (#527) --------- Co-authored-by: Filippo Olivo <filippo@filippoolivo.com> Co-authored-by: Giovanni Canali <115086358+GiovanniCanali@users.noreply.github.com> Co-authored-by: giovanni <giovanni.canali98@yahoo.it> Co-authored-by: AleDinve <giuseppealessio.d@student.unisi.it>
2025-06-13 17:34:37 +02:00
parent 6b355b45de
commit 7bf7d34d0f
40 changed files with 1963 additions and 581 deletions
--- a/tests/test_messagepassing/test_interaction_network_block.py
+++ b/tests/test_messagepassing/test_interaction_network_block.py
@@ -0,0 +1,84 @@
+import pytest
+import torch
+from pina.model.block.message_passing import InteractionNetworkBlock
+
+# Data for testing
+x = torch.rand(10, 3)
+edge_index = torch.randint(0, 10, (2, 20))
+edge_attr = torch.randn(20, 2)
+
+
+@pytest.mark.parametrize("node_feature_dim", [1, 3])
+@pytest.mark.parametrize("edge_feature_dim", [0, 2])
+def test_constructor(node_feature_dim, edge_feature_dim):
+
+    InteractionNetworkBlock(
+        node_feature_dim=node_feature_dim,
+        edge_feature_dim=edge_feature_dim,
+        hidden_dim=64,
+        n_message_layers=2,
+        n_update_layers=2,
+    )
+
+    # Should fail if node_feature_dim is negative
+    with pytest.raises(AssertionError):
+        InteractionNetworkBlock(node_feature_dim=-1)
+
+    # Should fail if edge_feature_dim is negative
+    with pytest.raises(AssertionError):
+        InteractionNetworkBlock(node_feature_dim=3, edge_feature_dim=-1)
+
+    # Should fail if hidden_dim is negative
+    with pytest.raises(AssertionError):
+        InteractionNetworkBlock(node_feature_dim=3, hidden_dim=-1)
+
+    # Should fail if n_message_layers is negative
+    with pytest.raises(AssertionError):
+        InteractionNetworkBlock(node_feature_dim=3, n_message_layers=-1)
+
+    # Should fail if n_update_layers is negative
+    with pytest.raises(AssertionError):
+        InteractionNetworkBlock(node_feature_dim=3, n_update_layers=-1)
+
+
+@pytest.mark.parametrize("edge_feature_dim", [0, 2])
+def test_forward(edge_feature_dim):
+
+    model = InteractionNetworkBlock(
+        node_feature_dim=x.shape[1],
+        edge_feature_dim=edge_feature_dim,
+        hidden_dim=64,
+        n_message_layers=2,
+        n_update_layers=2,
+    )
+
+    if edge_feature_dim == 0:
+        output_ = model(edge_index=edge_index, x=x)
+    else:
+        output_ = model(edge_index=edge_index, x=x, edge_attr=edge_attr)
+    assert output_.shape == x.shape
+
+
+@pytest.mark.parametrize("edge_feature_dim", [0, 2])
+def test_backward(edge_feature_dim):
+
+    model = InteractionNetworkBlock(
+        node_feature_dim=x.shape[1],
+        edge_feature_dim=edge_feature_dim,
+        hidden_dim=64,
+        n_message_layers=2,
+        n_update_layers=2,
+    )
+
+    if edge_feature_dim == 0:
+        output_ = model(edge_index=edge_index, x=x.requires_grad_())
+    else:
+        output_ = model(
+            edge_index=edge_index,
+            x=x.requires_grad_(),
+            edge_attr=edge_attr.requires_grad_(),
+        )
+
+    loss = torch.mean(output_)
+    loss.backward()
+    assert x.grad.shape == x.shape