Automatically register custom cvxpy method

README.md

@@ -6,7 +6,7 @@ This generated solver is specific to the problem family and accepts different pa
 In particular, this solver is suitable for deployment on embedded systems.
 In addition, CVXPYgen creates a Python wrapper for prototyping and desktop (non-embedded) applications.
 
-An overview of CVXPYgen can be found in our [manuscript](https://web.stanford.edu/~boyd/papers/cvxpygen.html).
+An overview of CVXPYgen can be found in our [slides and manuscript](https://web.stanford.edu/~boyd/papers/cvxpygen.html).
 
 CVXPYgen accepts CVXPY problems that are compliant with [Disciplined Convex Programming (DCP)](https://www.cvxpy.org/tutorial/dcp/index.html).
 DCP is a system for constructing mathematical expressions with known curvature from a given library of base functions. 
@@ -118,7 +118,7 @@ import sys
 
 # import extension module and register custom CVXPY solve method
 from nonneg_LS.cpg_solver import cpg_solve
-problem.register_solve('cpg', cpg_solve)
+problem.register_solve('CPG', cpg_solve)
 
 # solve problem conventionally
 t0 = time.time()
@@ -131,7 +131,7 @@ sys.stdout.write('Objective function value: %.6f\n' % val)
 
 # solve problem with C code via python wrapper
 t0 = time.time()
-val = problem.solve(method='cpg', updated_params=['A', 'b'], verbose=False)
+val = problem.solve(method='CPG', updated_params=['A', 'b'], verbose=False)
 t1 = time.time()
 sys.stdout.write('\nCVXPYgen\nSolve time: %.3f ms\n' % (1000 * (t1 - t0)))
 sys.stdout.write('Primal solution: x = [%.6f, %.6f]\n' % tuple(x.value))
@@ -148,7 +148,7 @@ Here, we use `verbose=False` to suppress printing.
 The list of changeable settings differs by solver and is documented in `<code_dir>/README.html` after code generation.
 
 Comparing the standard and codegen methods for this example, both the solutions and objective values are close.
-Especially for smaller problems like this, the new solve method ``'cpg'`` is significantly faster than solving without code generation.
+Especially for smaller problems like this, the new solve method ``'CPG'`` is significantly faster than solving without code generation.
 
 ### 3. Executable
 

cvxpygen/cpg.py

@@ -16,6 +16,7 @@
 import shutil
 import pickle
 import warnings
+import importlib
 
 from cvxpygen import utils
 from cvxpygen.utils import write_file, read_write_file, write_example_def, write_module_prot, write_module_def, \
@@ -89,6 +90,9 @@ def generate_code(problem, code_dir='CPG_code', solver=None, solver_opts=None,
 
     if wrapper:
         compile_python_module(code_dir)
+        module = importlib.import_module(f'{code_dir}.cpg_solver')
+        cpg_solve = getattr(module, 'cpg_solve')
+        problem.register_solve('CPG', cpg_solve)
 
 
 def get_quad_obj(problem, solver_type, solver_opts, solver_class) -> bool:

cvxpygen/utils.py

@@ -41,6 +41,7 @@ def write_vec_def(f, vec, name, typ):
     """
     Write vector to file
     """
+    vec = replace_inf(vec)
     f.write(f'{typ} {name}[{len(vec)}] = {{\n')
 
     # Write vector components
@@ -260,7 +261,7 @@ def write_param_def(f, param, name, prefix, suffix):
         if name.isupper():
             write_mat_def(f, param, f'{prefix}canon_{name}{suffix}')
         elif name == 'd':
-            f.write(f'cpg_float {prefix}canon_d{suffix} = %.20f;\n' % param[0])
+            f.write(f'cpg_float {prefix}canon_d{suffix} = %.20f;\n' % replace_inf(param[0]))
         else:
             write_vec_def(f, param, f'{prefix}canon_{name}{suffix}', 'cpg_float')
         f.write('\n')
@@ -463,9 +464,9 @@ def write_workspace_def(f, configuration, variable_info, dual_variable_info, par
         if p_id == 'd':
             canon_casts.append('')
         else:
-            write_param_def(f, replace_inf(p), p_id, configuration.prefix, '')
+            write_param_def(f, p, p_id, configuration.prefix, '')
             if solver_interface.inmemory_preconditioning:
-                write_param_def(f, replace_inf(p), p_id, configuration.prefix, '_conditioning')
+                write_param_def(f, p, p_id, configuration.prefix, '_conditioning')
             if p_id.isupper():
                 canon_casts.append('')
             else:

examples/main.py

@@ -34,10 +34,6 @@
     2. Solve & Compare
     '''
 
-    # import extension module and register custom CVXPY solve method
-    from nonneg_LS.cpg_solver import cpg_solve
-    problem.register_solve('cpg', cpg_solve)
-
     # solve problem conventionally
     t0 = time.time()
     val = problem.solve(solver='SCS')
@@ -49,7 +45,7 @@
 
     # solve problem with C code via python wrapper
     t0 = time.time()
-    val = problem.solve(method='cpg', updated_params=['A', 'b'], verbose=False)
+    val = problem.solve(method='CPG', updated_params=['A', 'b'], verbose=False)
     t1 = time.time()
     sys.stdout.write('\nCVXPYgen\nSolve time: %.3f ms\n' % (1000 * (t1 - t0)))
     sys.stdout.write('Primal solution: x = [%.6f, %.6f]\n' % tuple(x.value))

setup.py

@@ -3,7 +3,7 @@
 
 MAJOR = 0
 MINOR = 3
-MICRO = 5
+MICRO = 6
 VERSION = '%d.%d.%d' % (MAJOR, MINOR, MICRO)
 
 

tests/test_E2E_LP.py

@@ -125,8 +125,8 @@ def test(name, solver, style, seed):
     with open('test_%s_%s_%s/problem.pickle' % (name, solver, style), 'rb') as f:
         prob = pickle.load(f)
 
-    module = importlib.import_module('test_%s_%s_%s.cpg_solver' % (name, solver, style))
-    prob.register_solve('CPG', module.cpg_solve)
+    #module = importlib.import_module('test_%s_%s_%s.cpg_solver' % (name, solver, style))
+    #prob.register_solve('CPG', module.cpg_solve)
 
     prob = assign_data(prob, name, seed)
 

tests/test_E2E_QP.py

@@ -203,8 +203,8 @@ def test(name, solver, style, seed):
     with open('test_%s_%s_%s/problem.pickle' % (name, solver, style), 'rb') as f:
         prob = pickle.load(f)
 
-    module = importlib.import_module('test_%s_%s_%s.cpg_solver' % (name, solver, style))
-    prob.register_solve('CPG', module.cpg_solve)
+    #module = importlib.import_module('test_%s_%s_%s.cpg_solver' % (name, solver, style))
+    #prob.register_solve('CPG', module.cpg_solve)
 
     prob = assign_data(prob, name, seed)
 

tests/test_E2E_SOCP.py

@@ -100,8 +100,8 @@ def test(name, solver, style, seed):
     with open('test_%s_%s_%s/problem.pickle' % (name, solver, style), 'rb') as f:
         prob = pickle.load(f)
 
-    module = importlib.import_module('test_%s_%s_%s.cpg_solver' % (name, solver, style))
-    prob.register_solve('CPG', module.cpg_solve)
+    #module = importlib.import_module('test_%s_%s_%s.cpg_solver' % (name, solver, style))
+    #prob.register_solve('CPG', module.cpg_solve)
 
     prob = assign_data(prob, name, seed)