renaming

tests/test_model/test_feed_forward.py

@@ -0,0 +1,46 @@
+import torch
+import pytest
+
+from pina.model import FeedForward
+
+data = torch.rand((20, 3))
+input_vars = 3
+output_vars = 4
+
+
+def test_constructor():
+    FeedForward(input_vars, output_vars)
+    FeedForward(input_vars, output_vars, inner_size=10, n_layers=20)
+    FeedForward(input_vars, output_vars, layers=[10, 20, 5, 2])
+    FeedForward(input_vars,
+                output_vars,
+                layers=[10, 20, 5, 2],
+                func=torch.nn.ReLU)
+    FeedForward(input_vars,
+                output_vars,
+                layers=[10, 20, 5, 2],
+                func=[torch.nn.ReLU, torch.nn.ReLU, None, torch.nn.Tanh])
+
+
+def test_constructor_wrong():
+    with pytest.raises(RuntimeError):
+        FeedForward(input_vars,
+                    output_vars,
+                    layers=[10, 20, 5, 2],
+                    func=[torch.nn.ReLU, torch.nn.ReLU])
+
+
+def test_forward():
+    dim_in, dim_out = 3, 2
+    fnn = FeedForward(dim_in, dim_out)
+    output_ = fnn(data)
+    assert output_.shape == (data.shape[0], dim_out)
+
+def test_backward():
+    dim_in, dim_out = 3, 2
+    fnn = FeedForward(dim_in, dim_out)
+    data.requires_grad = True
+    output_ = fnn(data)
+    l=torch.mean(output_)
+    l.backward()
+    assert data._grad.shape == torch.Size([20,3])