Loss Fixing #182 (#184)

* fix doc loss + adding PowerLoss
* adding loss tests folder

---------

Co-authored-by: Dario Coscia <dariocoscia@Dario-Coscia.local>

tests/test_loss/test_powerloss.py

@@ -0,0 +1,49 @@
+import torch
+import pytest
+
+from pina.loss import PowerLoss
+
+input = torch.tensor([[3.], [1.], [-8.]])
+target = torch.tensor([[6.], [4.], [2.]])
+available_reductions = ['str', 'mean', 'none']
+
+
+def test_PowerLoss_constructor():
+    # test reduction
+    for reduction in available_reductions:
+        PowerLoss(reduction=reduction)
+    # test p
+    for p in [float('inf'), -float('inf'), 1, 10, -8]:
+        PowerLoss(p=p)
+
+def test_PowerLoss_forward():
+    # l2 loss
+    loss = PowerLoss(p=2, reduction='mean')
+    l2_loss = torch.mean((input-target).pow(2))
+    assert loss(input, target) == l2_loss
+    # l1 loss
+    loss = PowerLoss(p=1, reduction='sum')
+    l1_loss = torch.sum(torch.abs(input-target))
+    assert loss(input, target) == l1_loss
+
+def test_LpRelativeLoss_constructor():
+    # test reduction
+    for reduction in available_reductions:
+        PowerLoss(reduction=reduction, relative=True)
+    # test p
+    for p in [float('inf'), -float('inf'), 1, 10, -8]:
+        PowerLoss(p=p,relative=True)
+
+def test_LpRelativeLoss_forward():
+    # l2 relative loss
+    loss = PowerLoss(p=2, reduction='mean',relative=True)
+    l2_loss = (input-target).pow(2)/input.pow(2)
+    assert loss(input, target) == torch.mean(l2_loss)
+    # l1 relative loss
+    loss = PowerLoss(p=1, reduction='sum',relative=True)
+    l1_loss = torch.abs(input-target)/torch.abs(input)
+    assert loss(input, target) == torch.sum(l1_loss)
+
+
+
+