cvxopt_forced

multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CQBoostUtils.py

@@ -186,7 +186,7 @@ class ColumnGenerationClassifier(BaseEstimator, ClassifierMixin, BaseBoost):
         if previous_w is not None:
             qp.initial_values = np.append(previous_w, [0])
 
-        try:
+        # try:
         solver_result = qp.solve(abstol=1e-10, reltol=1e-10, feastol=1e-10, return_all_information=True)
         w = np.asarray(np.array(solver_result['x']).T[0])[:n_hypotheses]
 
@@ -200,17 +200,17 @@ class ColumnGenerationClassifier(BaseEstimator, ClassifierMixin, BaseBoost):
             self.dual_constraint_rhs = dual_variables[-1]
             # logging.info('Updating dual constraint rhs: {}'.format(self.dual_constraint_rhs))
 
-        except:
-            logging.warning('QP Solving failed at iteration {}.'.format(n_hypotheses))
-            if previous_w is not None:
-                w = np.append(previous_w, [0])
-            else:
-                w = np.array([1.0 / n_hypotheses] * n_hypotheses)
-
-            if previous_alpha is not None:
-                alpha = previous_alpha
-            else:
-                alpha = self._initialize_alphas(n_examples)
+        # except:
+        #     logging.warning('QP Solving failed at iteration {}.'.format(n_hypotheses))
+        #     if previous_w is not None:
+        #         w = np.append(previous_w, [0])
+        #     else:
+        #         w = np.array([1.0 / n_hypotheses] * n_hypotheses)
+        #
+        #     if previous_alpha is not None:
+        #         alpha = previous_alpha
+        #     else:
+        #         alpha = self._initialize_alphas(n_examples)
 
         return w, alpha
 

multiview_platform/Versions.py

@@ -13,6 +13,12 @@ def testVersions():
     except ImportError:
         raise
 
+    try:
+        import cvxopt
+    except ImportError:
+        isUpToDate = False
+        toInstall.append("cvxopt")
+
     try:
         import pyscm
     except ImportError: