use LabelTensor, fix minor, docs

tests/test_deeponet.py

@@ -0,0 +1,26 @@
+import torch
+import pytest
+
+from pina import LabelTensor
+from pina.model import DeepONet, FeedForward as FFN
+
+
+data = torch.rand((20, 3))
+input_vars = ['a', 'b', 'c']
+output_vars = ['d']
+input_ = LabelTensor(data, input_vars)
+
+
+def test_constructor():
+    branch = FFN(input_variables=['a', 'c'], output_variables=20)
+    trunk = FFN(input_variables=['b'], output_variables=20)
+    onet = DeepONet(trunk_net=trunk, branch_net=branch,
+                    output_variables=output_vars)
+
+def test_forward():
+    branch = FFN(input_variables=['a', 'c'], output_variables=10)
+    trunk = FFN(input_variables=['b'], output_variables=10)
+    onet = DeepONet(trunk_net=trunk, branch_net=branch,
+                    output_variables=output_vars)
+    output_ = onet(input_)
+    assert output_.labels == output_vars