Fix Codacy Warnings (#477)

---------

Co-authored-by: Dario Coscia <dariocos99@gmail.com>

pina/solver/physic_informed_solver/__init__.py

@@ -1,3 +1,5 @@
+"""TODO"""
+
 __all__ = [
     "PINNInterface",
     "PINN",

pina/solver/physic_informed_solver/causal_pinn.py

@@ -2,9 +2,9 @@
 
 import torch
 
-from pina.problem import TimeDependentProblem
+from ...problem import TimeDependentProblem
 from .pinn import PINN
-from pina.utils import check_consistency
+from ...utils import check_consistency
 
 
 class CausalPINN(PINN):

pina/solver/physic_informed_solver/competitive_pinn.py

@@ -1,7 +1,7 @@
 """Module for Competitive PINN."""
 
-import torch
 import copy
+import torch
 
 from ...problem import InverseProblem
 from .pinn_interface import PINNInterface

pina/solver/physic_informed_solver/gradient_pinn.py

@@ -3,8 +3,8 @@
 import torch
 
 from .pinn import PINN
-from pina.operator import grad
-from pina.problem import SpatialProblem
+from ...operator import grad
+from ...problem import SpatialProblem
 
 
 class GradientPINN(PINN):
@@ -32,7 +32,7 @@ class GradientPINN(PINN):
         \mathcal{L}_{\rm{problem}} =& \frac{1}{N}\sum_{i=1}^N
         \mathcal{L}(\mathcal{A}[\mathbf{u}](\mathbf{x}_i)) +
         \frac{1}{N}\sum_{i=1}^N
-        \mathcal{L}(\mathcal{B}[\mathbf{u}](\mathbf{x}_i)) + \\
+        \mathcal{L}(\mathcal{B}[\mathbf{u}](\mathbf{x}_i)) + 
         &\frac{1}{N}\sum_{i=1}^N
         \nabla_{\mathbf{x}}\mathcal{L}(\mathcal{A}[\mathbf{u}](\mathbf{x}_i)) +
         \frac{1}{N}\sum_{i=1}^N

pina/solver/physic_informed_solver/pinn_interface.py

@@ -106,7 +106,6 @@ class PINNInterface(SolverInterface, metaclass=ABCMeta):
             samples and equation.
         :rtype: LabelTensor
         """
-        pass
 
     def compute_residual(self, samples, equation):
         """

pina/solver/physic_informed_solver/self_adaptive_pinn.py

@@ -1,10 +1,10 @@
 """Module for Self-Adaptive PINN."""
 
-import torch
 from copy import deepcopy
+import torch
 
-from pina.utils import check_consistency
-from pina.problem import InverseProblem
+from ...utils import check_consistency
+from ...problem import InverseProblem
 from ..solver import MultiSolverInterface
 from .pinn_interface import PINNInterface
 
@@ -155,7 +155,7 @@ class SelfAdaptivePINN(PINNInterface, MultiSolverInterface):
         self._vectorial_loss.reduction = "none"
 
     def forward(self, x):
-        """
+        r"""
         Forward pass implementation for the PINN
         solver. It returns the function
         evaluation :math:`\mathbf{u}(\mathbf{x})` at the control points