Fix an error when rebasing on main

Gurobi · Oct 30, 2023 · b54ec02 · b54ec02
1 parent 06fa8e7
commit b54ec02
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Showing 2 changed files with 17 additions and 14 deletions.
diff --git a/notebooks/adversarial/adversarial_logistic_regression.ipynb b/notebooks/adversarial/adversarial_logistic_regression.ipynb
@@ -49,6 +49,15 @@
     "%pip install -U ../../"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install -i https://pypi.anaconda.org/gurobi-machinelearning-wheels-staging/simple gurobi-machinelearning==1.2.0.dev5"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -129,7 +138,7 @@
    },
    "outputs": [],
    "source": [
-    "ex_prob.shape"
+    "from gurobi_ml.sklearn.logistic_regression import LogisticRegressionConstr"
    ]
   },
   {
@@ -140,19 +149,17 @@
    },
    "outputs": [],
    "source": [
-    "from gurobi_ml.sklearn.logistic_regression import LogisticRegressionConstr"
+    "pwl_attr = LogisticRegressionConstr.default_pwl_attributes()\n",
+    "pwl_attr"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "pwl_attr = LogisticRegressionConstr.default_pwl_attributes()\n",
-    "pwl_attr"
+    "pwl_attr['FuncNonLinear'] = 1"
    ]
   },
   {
@@ -267,11 +274,6 @@
    },
    "outputs": [],
    "source": [
-    "m.Params.NonConvex = 2\n",
-    "m.Params.Obbt = 3\n",
-    "m.Params.PreSos1BigM = 1e6\n",
-    "m.Params.PreSos2BigM = 1e6\n",
-    "m.Params.PreSos2Encoding = 3\n",
     "m.optimize()"
    ]
   },

diff --git a/src/gurobi_ml/sklearn/logistic_regression.py b/src/gurobi_ml/sklearn/logistic_regression.py
@@ -226,8 +226,9 @@ def _multi_class_model(self, **kwargs):
         outputvars = self._output
         coefs = self.predictor.coef_
         intercept = self.predictor.intercept_
-        self._create_output_vars(self._input, name="affine_trans")
-        affinevars = self._output
+        affinevars = self._gp_model.addMVar(
+            self.output.shape, lb=-gp.GRB.INFINITY, name="affine_trans"
+        )
         self.affinevars = affinevars
         self.gp_model.addConstr(
             affinevars == self.input @ coefs.T + intercept, name="linreg"