remove comments from LogReg

intel · Nov 15, 2024 · 5a2f6b7 · 5a2f6b7
1 parent 9825642
commit 5a2f6b7
Showing 1 changed file with 0 additions and 11 deletions.
diff --git a/sklearnex/linear_model/logistic_regression.py b/sklearnex/linear_model/logistic_regression.py
@@ -289,7 +289,6 @@ def _onedal_fit(self, X, y, sample_weight=None, queue=None):
             if queue is None or queue.sycl_device.is_cpu:
                 return self._onedal_cpu_fit(X, y, sample_weight)
 
-            #  coverage: gpu_start
             assert sample_weight is None
 
             if sklearn_check_version("1.0"):
@@ -326,13 +325,11 @@ def _onedal_fit(self, X, y, sample_weight=None, queue=None):
             else:
                 self._onedal_estimator.fit(X, y, queue=queue)
                 self._save_attributes()
-            #  coverage: gpu_stop
 
         def _onedal_predict(self, X, queue=None):
             if queue is None or queue.sycl_device.is_cpu:
                 return daal4py_predict(self, X, "computeClassLabels")
 
-            #  coverage: gpu_start
             if sklearn_check_version("1.0"):
                 X = validate_data(
                     self,
@@ -353,13 +350,10 @@ def _onedal_predict(self, X, queue=None):
             assert hasattr(self, "_onedal_estimator")
             return self._onedal_estimator.predict(X, queue=queue)
 
-        #  coverage: gpu_stop
-
         def _onedal_predict_proba(self, X, queue=None):
             if queue is None or queue.sycl_device.is_cpu:
                 return daal4py_predict(self, X, "computeClassProbabilities")
 
-            #  coverage: gpu_start
             if sklearn_check_version("1.0"):
                 X = validate_data(
                     self,
@@ -380,13 +374,10 @@ def _onedal_predict_proba(self, X, queue=None):
             assert hasattr(self, "_onedal_estimator")
             return self._onedal_estimator.predict_proba(X, queue=queue)
 
-        #  coverage: gpu_stop
-
         def _onedal_predict_log_proba(self, X, queue=None):
             if queue is None or queue.sycl_device.is_cpu:
                 return daal4py_predict(self, X, "computeClassLogProbabilities")
 
-            #  coverage: gpu_start
             if sklearn_check_version("1.0"):
                 X = validate_data(
                     self,
@@ -407,8 +398,6 @@ def _onedal_predict_log_proba(self, X, queue=None):
             assert hasattr(self, "_onedal_estimator")
             return self._onedal_estimator.predict_log_proba(X, queue=queue)
 
-        #  coverage: gpu_stop
-
         fit.__doc__ = _sklearn_LogisticRegression.fit.__doc__
         predict.__doc__ = _sklearn_LogisticRegression.predict.__doc__
         predict_proba.__doc__ = _sklearn_LogisticRegression.predict_proba.__doc__