Fixing gael's comments

NelleV · NelleV · commit 34596c6dc127 · 2018-06-01T16:46:01.000-07:00
diff --git a/benchmarks/bench_saga.py b/benchmarks/bench_saga.py
@@ -160,7 +160,6 @@ def exp(solvers, penalty, single_target,
     X = X[:n_samples]
     y = y[:n_samples]
 
-    # cached_fit = mem.cache(fit_single)
     out = Parallel(n_jobs=n_jobs, mmap_mode=None)(
         delayed(fit_single)(solver, X, y,
                             penalty=penalty, single_target=single_target,
diff --git a/sklearn/linear_model/logistic.py b/sklearn/linear_model/logistic.py
@@ -1197,6 +1197,10 @@ def fit(self, X, y, sample_weight=None):
         Returns
         -------
         self : object
+
+        Notes
+        -----
+        The SAGA solver supports both float64 and float32 bit arrays.
         """
         if not isinstance(self.C, numbers.Number) or self.C < 0:
             raise ValueError("Penalty term must be positive; got (C=%r)"
diff --git a/sklearn/linear_model/sag_fast.pyx.tp b/sklearn/linear_model/sag_fast.pyx.tp
@@ -267,16 +267,6 @@ def sag{{name}}(SequentialDataset{{name}} dataset,
     cdef {{c_type}} y
     # the sample weight
     cdef {{c_type}} sample_weight
-    # # _step_size
-    # cdef {{c_type}} _step_size = <{{c_type}}> __step_size
-    # # alpha
-    # cdef {{c_type}} alpha = <{{c_type}}> _alpha
-    # # beta
-    # cdef {{c_type}} beta = <{{c_type}}> _beta
-    # # tol
-    # cdef {{c_type}} tol = <{{c_type}}> _tol
-    # # intercept_decay
-    # cdef {{c_type}} intercept_decay = <{{c_type}}> _intercept_decay
 
     # helper variable for indexes
     cdef int f_idx, s_idx, feature_ind, class_ind, j
