remove inverse diffusion-reaction

Author: GiovanniCanali

pina/problem/zoo/__init__.py

@@ -8,7 +8,6 @@
     "Poisson2DSquareProblem",
     "DiffusionReactionProblem",
     "InversePoisson2DSquareProblem",
-    "InverseDiffusionReactionProblem",
 ]
 
 from .supervised_problem import SupervisedProblem
@@ -18,4 +17,3 @@
 from .poisson_2d_square import Poisson2DSquareProblem
 from .diffusion_reaction import DiffusionReactionProblem
 from .inverse_poisson_2d_square import InversePoisson2DSquareProblem
-from .inverse_diffusion_reaction import InverseDiffusionReactionProblem

pina/problem/zoo/inverse_diffusion_reaction.py

@@ -6,10 +6,7 @@
 from pina.solver import CausalPINN
 from pina.trainer import Trainer
 from pina.model import FeedForward
-from pina.problem.zoo import (
-    DiffusionReactionProblem,
-    InverseDiffusionReactionProblem,
-)
+from pina.problem.zoo import DiffusionReactionProblem
 from pina.condition import (
     InputTargetCondition,
     InputEquationCondition,
@@ -31,8 +28,6 @@ class DummySpatialProblem(SpatialProblem):
 # define problems
 problem = DiffusionReactionProblem()
 problem.discretise_domain(50)
-inverse_problem = InverseDiffusionReactionProblem()
-inverse_problem.discretise_domain(50)
 
 # add input-output condition to test supervised learning
 input_pts = torch.rand(50, len(problem.input_variables))
@@ -45,7 +40,7 @@ class DummySpatialProblem(SpatialProblem):
 model = FeedForward(len(problem.input_variables), len(problem.output_variables))
 
 
-@pytest.mark.parametrize("problem", [problem, inverse_problem])
+@pytest.mark.parametrize("problem", [problem])
 @pytest.mark.parametrize("eps", [100, 100.1])
 def test_constructor(problem, eps):
     with pytest.raises(ValueError):
@@ -59,7 +54,7 @@ def test_constructor(problem, eps):
     )
 
 
-@pytest.mark.parametrize("problem", [problem, inverse_problem])
+@pytest.mark.parametrize("problem", [problem])
 @pytest.mark.parametrize("batch_size", [None, 1, 5, 20])
 @pytest.mark.parametrize("compile", [True, False])
 def test_solver_train(problem, batch_size, compile):
@@ -79,7 +74,7 @@ def test_solver_train(problem, batch_size, compile):
         assert isinstance(solver.model, OptimizedModule)
 
 
-@pytest.mark.parametrize("problem", [problem, inverse_problem])
+@pytest.mark.parametrize("problem", [problem])
 @pytest.mark.parametrize("batch_size", [None, 1, 5, 20])
 @pytest.mark.parametrize("compile", [True, False])
 def test_solver_validation(problem, batch_size, compile):
@@ -99,7 +94,7 @@ def test_solver_validation(problem, batch_size, compile):
         assert isinstance(solver.model, OptimizedModule)
 
 
-@pytest.mark.parametrize("problem", [problem, inverse_problem])
+@pytest.mark.parametrize("problem", [problem])
 @pytest.mark.parametrize("batch_size", [None, 1, 5, 20])
 @pytest.mark.parametrize("compile", [True, False])
 def test_solver_test(problem, batch_size, compile):
@@ -119,7 +114,7 @@ def test_solver_test(problem, batch_size, compile):
         assert isinstance(solver.model, OptimizedModule)
 
 
-@pytest.mark.parametrize("problem", [problem, inverse_problem])
+@pytest.mark.parametrize("problem", [problem])
 def test_train_load_restore(problem):
     dir = "tests/test_solver/tmp"
     problem = problem