return flat list of distinct constraints in benchmarks

Author: Dimosts

pycona/benchmarks/exam_timetabling.py

@@ -2,7 +2,7 @@
 
 from ..answering_queries.constraint_oracle import ConstraintOracle
 from ..problem_instance import ProblemInstance, absvar
-
+from cpmpy.transformations.normalize import toplevel_list
 
 def day_of_exam(course, slots_per_day):
     return course // slots_per_day
@@ -27,7 +27,7 @@ def construct_examtt_simple(nsemesters=9, courses_per_semester=6, slots_per_day=
     for row in courses:
         model += cp.AllDifferent(day_of_exam(row, slots_per_day)).decompose()
 
-    C_T = list(model.constraints)
+    C_T = list(set(toplevel_list(model.constraints)))
 
     if model.solve():
         courses.clear()

pycona/benchmarks/job_shop_scheduling.py

@@ -3,7 +3,7 @@
 import cpmpy as cp
 import numpy as np
 from cpmpy.expressions.utils import all_pairs
-
+from cpmpy.transformations.normalize import toplevel_list
 from ..answering_queries.constraint_oracle import ConstraintOracle
 from ..problem_instance import ProblemInstance, absvar
 
@@ -56,7 +56,7 @@ def construct_job_shop_scheduling_problem(n_jobs, machines, horizon, seed=0):
         for (j1, t1), (j2, t2) in all_pairs(zip(*tasks_on_mach)):
             m += (end[j1, t1] <= start[j2, t2]) | (end[j2, t2] <= start[j1, t1])
 
-    C_T = list(model.constraints)
+    C_T = list(set(toplevel_list(model.constraints)))
 
     max_duration = max(duration)
 

pycona/benchmarks/jsudoku.py

@@ -1,5 +1,5 @@
 import cpmpy as cp
-
+from cpmpy.transformations.normalize import toplevel_list
 from ..answering_queries.constraint_oracle import ConstraintOracle
 from ..problem_instance import ProblemInstance, absvar
 
@@ -49,6 +49,6 @@ def construct_jsudoku():
 
     instance = ProblemInstance(variables=grid, params=parameters, language=lang, name="jsudoku")
 
-    oracle = ConstraintOracle(C_T)
+    oracle = ConstraintOracle(list(set(toplevel_list(C_T))))
 
     return instance, oracle

pycona/benchmarks/murder.py

@@ -1,6 +1,6 @@
 
 import cpmpy as cp
-
+from cpmpy.transformations.normalize import toplevel_list
 from ..answering_queries.constraint_oracle import ConstraintOracle
 from ..problem_instance import ProblemInstance, absvar
 
@@ -45,6 +45,6 @@ def construct_murder_problem():
 
     instance = ProblemInstance(variables=grid, language=lang, name="murder")
 
-    oracle = ConstraintOracle(C_T)
+    oracle = ConstraintOracle(list(set(toplevel_list(C_T))))
 
     return instance, oracle

pycona/benchmarks/nurse_rostering.py

@@ -1,5 +1,5 @@
 import cpmpy as cp
-
+from cpmpy.transformations.normalize import toplevel_list
 from ..answering_queries.constraint_oracle import ConstraintOracle
 from ..problem_instance import ProblemInstance, absvar
 
@@ -30,7 +30,7 @@ def construct_nurse_rostering(shifts_per_day=3, num_days=5, num_nurses=8, nurses
     if not model.solve():
         raise Exception("The problem has no solution")
 
-    C_T = list(model.constraints)
+    C_T = list(set(toplevel_list(model.constraints)))
 
     # Create the language:
     AV = absvar(2)  # create abstract vars - as many as maximum arity

pycona/benchmarks/sudoku.py

@@ -1,5 +1,5 @@
 import cpmpy as cp
-
+from cpmpy.transformations.normalize import toplevel_list
 from ..answering_queries.constraint_oracle import ConstraintOracle
 from ..problem_instance import ProblemInstance, absvar
 
@@ -29,7 +29,7 @@ def construct_sudoku(block_size_row, block_size_col, grid_size):
         for j in range(0, grid_size, block_size_col):
             model += cp.AllDifferent(grid[i:i + block_size_row, j:j + block_size_col]).decompose()  # python's indexing
 
-    C_T = list(model.constraints)
+    C_T = list(set(toplevel_list(model.constraints)))
 
     # Create the language:
     AV = absvar(2)  # create abstract vars - as many as maximum arity