refine the code according to second round comments

cpp/src/glm/qn_mg.cu

@@ -149,40 +149,6 @@ void qnFit(raft::handle_t& handle,
     handle, input_data, input_desc, labels, coef, pams, X_col_major, n_classes, f, num_iters);
 }
 
-/*
-void qnFit(const raft::handle_t &handle,
-           const qn_params& pams,
-           float* X,
-           bool X_col_major,
-           float *y,
-           int N,
-           int D,
-           int C,
-           float* w0,
-           float* f,
-           int* num_iters,
-           int n_samples,
-           int rank,
-           int n_ranks)
-{
-  qnFit_impl<float, int>(
-    handle,
-    pams,
-    X,
-    X_col_major,
-    y,
-    N,
-    D,
-    C,
-    w0,
-    f,
-    num_iters,
-    n_samples,
-    rank,
-    n_ranks);
-}
-*/
-
 };  // namespace opg
 };  // namespace GLM
 };  // namespace ML

python/cuml/tests/dask/test_dask_logistic_regression.py

@@ -152,8 +152,6 @@ def imp():
 
     client.run(imp)
 
-    import numpy as np
-
     X = np.array([(1, 2), (1, 3), (2, 1), (3, 1)], datatype)
     y = np.array([1.0, 1.0, 0.0, 0.0], datatype)
 
@@ -190,6 +188,7 @@ def imp():
         LogisticRegression as cumlLBFGS_dask,
     )
 
+    # set n_informative variable for calling sklearn.datasets.make_classification
     n_info = 5
     nrows = int(nrows)
     ncols = int(ncols)