log_10dbc142

***** Runner *****

· Creating environments
· Discovering benchmarks
·· Uninstalling from conda-py3.8-cython-joblib-numpy-pandas-scipy-threadpoolctl
·· Building 10dbc142 <main> for conda-py3.8-cython-joblib-numpy-pandas-scipy-threadpoolctl
·· Installing 10dbc142 <main> into conda-py3.8-cython-joblib-numpy-pandas-scipy-threadpoolctl
· Running 115 total benchmarks (1 commits * 1 environments * 115 benchmarks)
[  0.00%] · For scikit-learn commit 10dbc142 <main>:
[  0.00%] ·· Benchmarking conda-py3.8-cython-joblib-numpy-pandas-scipy-threadpoolctl
[  0.87%] ··· Setting up cluster:16                                           ok
[  0.87%] ··· cluster.KMeansBenchmark.peakmem_fit                             ok
[  0.87%] ··· ================ =========== ======== ===========
              --                                   init        
              ---------------------------- --------------------
               representation   algorithm   random   k-means++ 
              ================ =========== ======== ===========
                   dense          lloyd      150M       165M   
                   dense          elkan      186M       187M   
                   sparse         lloyd      242M       245M   
                   sparse         elkan      251M       252M   
              ================ =========== ======== ===========

[  1.74%] ··· cluster.KMeansBenchmark.peakmem_predict                         ok
[  1.74%] ··· ================ =========== ======== ===========
              --                                   init        
              ---------------------------- --------------------
               representation   algorithm   random   k-means++ 
              ================ =========== ======== ===========
                   dense          lloyd      137M       137M   
                   dense          elkan      137M       137M   
                   sparse         lloyd      145M       145M   
                   sparse         elkan      145M       145M   
              ================ =========== ======== ===========

[  2.61%] ··· cluster.KMeansBenchmark.peakmem_transform                       ok
[  2.61%] ··· ================ =========== ======== ===========
              --                                   init        
              ---------------------------- --------------------
               representation   algorithm   random   k-means++ 
              ================ =========== ======== ===========
                   dense          lloyd      170M       170M   
                   dense          elkan      170M       170M   
                   sparse         lloyd      170M       170M   
                   sparse         elkan      170M       170M   
              ================ =========== ======== ===========

[  3.48%] ··· cluster.KMeansBenchmark.time_fit                                ok
[  3.48%] ··· ================ =========== ============ ============
              --                                      init          
              ---------------------------- -------------------------
               representation   algorithm     random     k-means++  
              ================ =========== ============ ============
                   dense          lloyd      383±5ms      1.20±0s   
                   dense          elkan     1.76±0.01s    2.95±0s   
                   sparse         lloyd     1.00±0.1s    3.59±0.02s 
                   sparse         elkan     2.37±0.02s   4.34±0.05s 
              ================ =========== ============ ============

[  4.35%] ··· cluster.KMeansBenchmark.time_predict                            ok
[  4.35%] ··· ================ =========== ============ =============
              --                                      init           
              ---------------------------- --------------------------
               representation   algorithm     random      k-means++  
              ================ =========== ============ =============
                   dense          lloyd      8.05±2ms    6.24±0.06ms 
                   dense          elkan     6.58±0.4ms    6.16±0.2ms 
                   sparse         lloyd      14.8±6ms      25.9±6ms  
                   sparse         elkan      26.0±6ms      25.7±6ms  
              ================ =========== ============ =============

[  5.22%] ··· cluster.KMeansBenchmark.time_transform                          ok
[  5.22%] ··· ================ =========== ============ ============
              --                                      init          
              ---------------------------- -------------------------
               representation   algorithm     random     k-means++  
              ================ =========== ============ ============
                   dense          lloyd      140±1ms      140±1ms   
                   dense          elkan      138±1ms      140±1ms   
                   sparse         lloyd     4.06±0.04s   4.05±0.07s 
                   sparse         elkan     4.05±0.02s   4.05±0.03s 
              ================ =========== ============ ============

[  6.09%] ··· cluster.KMeansBenchmark.track_test_score                        ok
[  6.09%] ··· ================ =========== =========== =====================
               representation   algorithm      init                         
              ---------------- ----------- ----------- ---------------------
                   dense          lloyd       random     -4.109886169433594 
                   dense          lloyd     k-means++    -3.077857732772827 
                   dense          elkan       random     -4.109885215759277 
                   dense          elkan     k-means++   -3.0778582096099854 
                   sparse         lloyd       random    -0.9266619682312012 
                   sparse         lloyd     k-means++     -0.9249227643013  
                   sparse         elkan       random    -0.9266619682312012 
                   sparse         elkan     k-means++   -0.9249262809753418 
              ================ =========== =========== =====================

[  6.96%] ··· cluster.KMeansBenchmark.track_train_score                       ok
[  6.96%] ··· ================ =========== =========== =====================
               representation   algorithm      init                         
              ---------------- ----------- ----------- ---------------------
                   dense          lloyd       random    -4.1075520515441895 
                   dense          lloyd     k-means++   -3.0774283409118652 
                   dense          elkan       random    -4.1075520515441895 
                   dense          elkan     k-means++   -3.0774285793304443 
                   sparse         lloyd       random    -0.9227071404457092 
                   sparse         lloyd     k-means++    -0.922096312046051 
                   sparse         elkan       random    -0.9227071404457092 
                   sparse         elkan     k-means++   -0.9221000075340271 
              ================ =========== =========== =====================

[  7.83%] ··· Setting up cluster:65                                           ok
[  7.83%] ··· cluster.MiniBatchKMeansBenchmark.peakmem_fit                    ok
[  7.83%] ··· ================ ======== ===========
              --                       init        
              ---------------- --------------------
               representation   random   k-means++ 
              ================ ======== ===========
                   dense         138M       140M   
                   sparse        221M       224M   
              ================ ======== ===========

[  8.70%] ··· ...ter.MiniBatchKMeansBenchmark.peakmem_predict                 ok
[  8.70%] ··· ================ ======== ===========
              --                       init        
              ---------------- --------------------
               representation   random   k-means++ 
              ================ ======== ===========
                   dense         135M       135M   
                   sparse        150M       150M   
              ================ ======== ===========

[  9.57%] ··· ...r.MiniBatchKMeansBenchmark.peakmem_transform                 ok
[  9.57%] ··· ================ ======== ===========
              --                       init        
              ---------------- --------------------
               representation   random   k-means++ 
              ================ ======== ===========
                   dense         168M       168M   
                   sparse        170M       170M   
              ================ ======== ===========

[ 10.43%] ··· cluster.MiniBatchKMeansBenchmark.time_fit                       ok
[ 10.43%] ··· ================ ========== ============
              --                         init         
              ---------------- -----------------------
               representation    random    k-means++  
              ================ ========== ============
                   dense        324±2ms     347±4ms   
                   sparse       626±30ms   1.66±0.01s 
              ================ ========== ============

[ 11.30%] ··· cluster.MiniBatchKMeansBenchmark.time_predict                   ok
[ 11.30%] ··· ================ ============ ============
              --                          init          
              ---------------- -------------------------
               representation     random     k-means++  
              ================ ============ ============
                   dense        6.20±0.2ms   6.16±0.2ms 
                   sparse        20.9±9ms     36.4±8ms  
              ================ ============ ============

[ 12.17%] ··· cluster.MiniBatchKMeansBenchmark.time_transform                 ok
[ 12.17%] ··· ================ ============ ============
              --                          init          
              ---------------- -------------------------
               representation     random     k-means++  
              ================ ============ ============
                   dense        137±0.7ms    138±0.4ms  
                   sparse       8.08±0.02s   8.13±0.02s 
              ================ ============ ============

[ 13.04%] ··· ...er.MiniBatchKMeansBenchmark.track_test_score                 ok
[ 13.04%] ··· ================ =========== =====================
               representation      init                         
              ---------------- ----------- ---------------------
                   dense          random     -4.596621036529541 
                   dense        k-means++   -3.1085314750671387 
                   sparse         random    -0.9366871118545532 
                   sparse       k-means++   -0.9386959075927734 
              ================ =========== =====================

[ 13.91%] ··· ...r.MiniBatchKMeansBenchmark.track_train_score                 ok
[ 13.91%] ··· ================ ===================== ====================
              --                                  init                   
              ---------------- ------------------------------------------
               representation          random             k-means++      
              ================ ===================== ====================
                   dense         -4.584851264953613   -3.115997314453125 
                   sparse       -0.9323447346687317   -0.934399425983429 
              ================ ===================== ====================

[ 14.78%] ··· Setting up decomposition:41                                     ok
[ 14.78%] ··· ...tion.DictionaryLearningBenchmark.peakmem_fit                 ok
[ 14.78%] ··· =============== ====== ======
              --                  n_jobs   
              --------------- -------------
               fit_algorithm    1      4   
              =============== ====== ======
                    lars       164M   178M 
                     cd        164M   177M 
              =============== ====== ======

[ 15.65%] ··· ...ictionaryLearningBenchmark.peakmem_transform                 ok
[ 15.65%] ··· =============== ====== ======
              --                  n_jobs   
              --------------- -------------
               fit_algorithm    1      4   
              =============== ====== ======
                    lars       135M   136M 
                     cd        135M   135M 
              =============== ====== ======

[ 16.52%] ··· ...osition.DictionaryLearningBenchmark.time_fit                 ok
[ 16.52%] ··· =============== =========== ============
              --                       n_jobs         
              --------------- ------------------------
               fit_algorithm       1           4      
              =============== =========== ============
                    lars       18.9±0.3s   11.1±0.08s 
                     cd         669±30ms   3.17±0.6s  
              =============== =========== ============

[ 17.39%] ··· ...n.DictionaryLearningBenchmark.time_transform                 ok
[ 17.39%] ··· =============== ========== ==========
              --                      n_jobs       
              --------------- ---------------------
               fit_algorithm      1          4     
              =============== ========== ==========
                    lars       325±40ms   330±20ms 
                     cd        348±70ms   304±20ms 
              =============== ========== ==========

[ 18.26%] ··· ...DictionaryLearningBenchmark.track_test_score                 ok
[ 18.26%] ··· =============== ======== ======================
               fit_algorithm   n_jobs                        
              --------------- -------- ----------------------
                    lars         1      -0.07475552707910538 
                    lars         4      -0.07475553052041055 
                     cd          1      -0.07475553452968597 
                     cd          4      -0.07475553498821336 
              =============== ======== ======================

[ 19.13%] ··· ...ictionaryLearningBenchmark.track_train_score                 ok
[ 19.13%] ··· =============== ======== ======================
               fit_algorithm   n_jobs                        
              --------------- -------- ----------------------
                    lars         1      -0.07231885939836502 
                    lars         4      -0.07231886145064417 
                     cd          1      -0.07231885939836502 
                     cd          4      -0.07231886156130721 
              =============== ======== ======================

[ 20.00%] ··· Setting up decomposition:75                                     ok
[ 20.00%] ··· ...BatchDictionaryLearningBenchmark.peakmem_fit                 ok
[ 20.00%] ··· =============== ====== ======
              --                  n_jobs   
              --------------- -------------
               fit_algorithm    1      4   
              =============== ====== ======
                    lars       155M   163M 
                     cd        153M   162M 
              =============== ====== ======

[ 20.87%] ··· ...ictionaryLearningBenchmark.peakmem_transform                 ok
[ 20.87%] ··· =============== ====== ======
              --                  n_jobs   
              --------------- -------------
               fit_algorithm    1      4   
              =============== ====== ======
                    lars       137M   136M 
                     cd        137M   136M 
              =============== ====== ======

[ 20.87%] ···· For parameters: 'lars', 1
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               
               For parameters: 'cd', 1
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(

[ 21.74%] ··· ...iniBatchDictionaryLearningBenchmark.time_fit                 ok
[ 21.74%] ··· =============== ============ ===========
              --                       n_jobs         
              --------------- ------------------------
               fit_algorithm       1            4     
              =============== ============ ===========
                    lars        11.4±0s     13.8±0.2s 
                     cd        3.13±0.01s   9.32±0.1s 
              =============== ============ ===========

[ 22.61%] ··· ...chDictionaryLearningBenchmark.time_transform                 ok
[ 22.61%] ··· =============== ========== ==========
              --                      n_jobs       
              --------------- ---------------------
               fit_algorithm      1          4     
              =============== ========== ==========
                    lars       333±40ms   295±20ms 
                     cd        315±40ms   320±20ms 
              =============== ========== ==========

[ 22.61%] ···· For parameters: 'lars', 1
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               
               For parameters: 'lars', 4
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               
               For parameters: 'cd', 1
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               
               For parameters: 'cd', 4
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(

[ 23.48%] ··· ...DictionaryLearningBenchmark.track_test_score                 ok
[ 23.48%] ··· =============== ======== ======================
               fit_algorithm   n_jobs                        
              --------------- -------- ----------------------
                    lars         1      -0.07506968826055527 
                    lars         4      -0.07506916151508632 
                     cd          1      -0.07509589940309525 
                     cd          4      -0.07509584120306487 
              =============== ======== ======================

[ 24.35%] ··· ...ictionaryLearningBenchmark.track_train_score                 ok
[ 24.35%] ··· =============== ======== ======================
               fit_algorithm   n_jobs                        
              --------------- -------- ----------------------
                    lars         1       -0.072443887591362  
                    lars         4      -0.07244402046391545 
                     cd          1      -0.07244545221328735 
                     cd          4      -0.07244553368477852 
              =============== ======== ======================

[ 24.35%] ···· For parameters: 'lars', 1
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(
               
               For parameters: 'cd', 1
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py:190: RuntimeWarning: Orthogonal matching pursuit ended prematurely due to linear dependence in the dictionary. The requested precision might not have been met.
                 new_code = orthogonal_mp_gram(

[ 25.22%] ··· Setting up decomposition:16                                     ok
[ 25.22%] ··· decomposition.PCABenchmark.peakmem_fit                          ok
[ 25.22%] ··· ============ ======
               svd_solver        
              ------------ ------
                  full      994M 
                 arpack     578M 
               randomized   609M 
              ============ ======

[ 26.09%] ··· decomposition.PCABenchmark.peakmem_transform                    ok
[ 26.09%] ··· ============ ======
               svd_solver        
              ------------ ------
                  full      551M 
                 arpack     551M 
               randomized   551M 
              ============ ======

[ 26.96%] ··· decomposition.PCABenchmark.time_fit                             ok
[ 26.96%] ··· ============ ==========
               svd_solver            
              ------------ ----------
                  full      1.88±0s  
                 arpack     810±10ms 
               randomized   736±5ms  
              ============ ==========

[ 27.83%] ··· decomposition.PCABenchmark.time_transform                       ok
[ 27.83%] ··· ============ =========
               svd_solver           
              ------------ ---------
                  full      167±5ms 
                 arpack     179±6ms 
               randomized   181±6ms 
              ============ =========

[ 28.70%] ··· decomposition.PCABenchmark.track_test_score                     ok
[ 28.70%] ··· ============ ====================
               svd_solver                      
              ------------ --------------------
                  full      0.744941771030426  
                 arpack     0.7449416518211365 
               randomized   0.744931161403656  
              ============ ====================

[ 29.57%] ··· decomposition.PCABenchmark.track_train_score                    ok
[ 29.57%] ··· ============ ====================
               svd_solver                      
              ------------ --------------------
                  full      0.7445714473724365 
                 arpack     0.7445658445358276 
               randomized   0.7445557713508606 
              ============ ====================

[ 30.43%] ··· Setting up ensemble:64                                          ok
[ 30.43%] ··· ...dientBoostingClassifierBenchmark.peakmem_fit                 ok
[ 30.43%] ··· ================ ======
               representation        
              ---------------- ------
                   dense        134M 
                   sparse       174M 
              ================ ======

[ 31.30%] ··· ...tBoostingClassifierBenchmark.peakmem_predict                 ok
[ 31.30%] ··· ================ ======
               representation        
              ---------------- ------
                   dense        131M 
                   sparse       141M 
              ================ ======

[ 32.17%] ··· ...GradientBoostingClassifierBenchmark.time_fit                 ok
[ 32.17%] ··· ================ ============
               representation              
              ---------------- ------------
                   dense        4.74±0.06s 
                   sparse       12.7±0.3s  
              ================ ============

[ 33.04%] ··· ...ientBoostingClassifierBenchmark.time_predict                 ok
[ 33.04%] ··· ================ ============
               representation              
              ---------------- ------------
                   dense        56.1±0.4ms 
                   sparse       51.7±0.5ms 
              ================ ============

[ 33.91%] ··· ...BoostingClassifierBenchmark.track_test_score                 ok
[ 33.91%] ··· ================ =====================
               representation                       
              ---------------- ---------------------
                   dense         0.5618424973930395 
                   sparse       0.10409974329281042 
              ================ =====================

[ 34.78%] ··· ...oostingClassifierBenchmark.track_train_score                 ok
[ 34.78%] ··· ================ =====================
               representation                       
              ---------------- ---------------------
                   dense         0.6261473617950604 
                   sparse       0.15180008167538628 
              ================ =====================

[ 35.65%] ··· Setting up ensemble:103                                         ok
[ 35.65%] ··· ...dientBoostingClassifierBenchmark.peakmem_fit               146M
[ 36.52%] ··· ...tBoostingClassifierBenchmark.peakmem_predict               134M
[ 37.39%] ··· ...GradientBoostingClassifierBenchmark.time_fit            2.46±0s
[ 38.26%] ··· ...ientBoostingClassifierBenchmark.time_predict           83.3±1ms
[ 39.13%] ··· ...BoostingClassifierBenchmark.track_test_score 0.7230709112942986
[ 40.00%] ··· ...oostingClassifierBenchmark.track_train_score 0.9812160155622751
[ 40.87%] ··· Setting up ensemble:24                                          ok
[ 40.87%] ··· ....RandomForestClassifierBenchmark.peakmem_fit                 ok
[ 40.87%] ··· ================ ====== ======
              --                   n_jobs   
              ---------------- -------------
               representation    1      4   
              ================ ====== ======
                   dense        213M   275M 
                   sparse       448M   615M 
              ================ ====== ======

[ 41.74%] ··· ...domForestClassifierBenchmark.peakmem_predict                 ok
[ 41.74%] ··· ================ ====== ======
              --                   n_jobs   
              ---------------- -------------
               representation    1      4   
              ================ ====== ======
                   dense        216M   222M 
                   sparse       432M   439M 
              ================ ====== ======

[ 42.61%] ··· ...ble.RandomForestClassifierBenchmark.time_fit                 ok
[ 42.61%] ··· ================ ============ ===========
              --                        n_jobs         
              ---------------- ------------------------
               representation       1            4     
              ================ ============ ===========
                   dense        11.5±0.4s    3.70±0.2s 
                   sparse       19.2±0.06s   5.18±0.1s 
              ================ ============ ===========

[ 43.48%] ··· ...RandomForestClassifierBenchmark.time_predict                 ok
[ 43.48%] ··· ================ ============ ==========
              --                        n_jobs        
              ---------------- -----------------------
               representation       1           4     
              ================ ============ ==========
                   dense        241±0.8ms    151±9ms  
                   sparse       1.85±0.01s   775±40ms 
              ================ ============ ==========

[ 44.35%] ··· ...omForestClassifierBenchmark.track_test_score                 ok
[ 44.35%] ··· ================ ==================== ====================
              --                                 n_jobs                 
              ---------------- -----------------------------------------
               representation           1                    4          
              ================ ==================== ====================
                   dense        0.7586980998861735   0.7586980998861735 
                   sparse       0.8656423941766682   0.8656423941766682 
              ================ ==================== ====================

[ 45.22%] ··· ...mForestClassifierBenchmark.track_train_score                 ok
[ 45.22%] ··· ================ ==================== ====================
              --                                 n_jobs                 
              ---------------- -----------------------------------------
               representation           1                    4          
              ================ ==================== ====================
                   dense        0.9964418089247236   0.9964418089247236 
                   sparse       0.9996123288718864   0.9996123288718864 
              ================ ==================== ====================

[ 46.09%] ··· Setting up linear_model:183                                     ok
[ 46.09%] ··· linear_model.ElasticNetBenchmark.peakmem_fit                    ok
[ 46.09%] ··· ================ ====== =======
              --                 precompute  
              ---------------- --------------
               representation   True   False 
              ================ ====== =======
                   dense        900M   1.25G 
                   sparse       167M    n/a  
              ================ ====== =======

[ 46.09%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 46.96%] ··· ...ar_model.ElasticNetBenchmark.peakmem_predict                 ok
[ 46.96%] ··· ================ ====== =======
              --                 precompute  
              ---------------- --------------
               representation   True   False 
              ================ ====== =======
                   dense        535M    535M 
                   sparse       108M    n/a  
              ================ ====== =======

[ 46.96%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 47.83%] ··· linear_model.ElasticNetBenchmark.time_fit                       ok
[ 47.83%] ··· ================ ============ =========
              --                     precompute      
              ---------------- ----------------------
               representation      True       False  
              ================ ============ =========
                   dense         1.45±0s     1.64±0s 
                   sparse       2.74±0.01s     n/a   
              ================ ============ =========

[ 47.83%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 48.70%] ··· linear_model.ElasticNetBenchmark.time_predict                   ok
[ 48.70%] ··· ================ ============ ============
              --                       precompute       
              ---------------- -------------------------
               representation      True        False    
              ================ ============ ============
                   dense        49.0±0.1ms   48.6±0.3ms 
                   sparse       2.62±0.2ms      n/a     
              ================ ============ ============

[ 48.70%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 49.57%] ··· ...r_model.ElasticNetBenchmark.track_test_score                 ok
[ 49.57%] ··· ================ ==================== ====================
              --                               precompute               
              ---------------- -----------------------------------------
               representation          True                False        
              ================ ==================== ====================
                   dense        0.9274010858287904   0.9274010851518739 
                   sparse       0.9502651165299631          n/a         
              ================ ==================== ====================

[ 49.57%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 50.43%] ··· ..._model.ElasticNetBenchmark.track_train_score                 ok
[ 50.43%] ··· ================ ==================== ====================
              --                               precompute               
              ---------------- -----------------------------------------
               representation          True                False        
              ================ ==================== ====================
                   dense        0.9276022549310393   0.9276022551143049 
                   sparse       0.956473959537393           n/a         
              ================ ==================== ====================

[ 50.43%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 51.30%] ··· Setting up linear_model:224                                     ok
[ 51.30%] ··· linear_model.LassoBenchmark.peakmem_fit                         ok
[ 51.30%] ··· ================ ====== =======
              --                 precompute  
              ---------------- --------------
               representation   True   False 
              ================ ====== =======
                   dense        900M   1.25G 
                   sparse       166M    n/a  
              ================ ====== =======

[ 51.30%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 52.17%] ··· linear_model.LassoBenchmark.peakmem_predict                     ok
[ 52.17%] ··· ================ ====== =======
              --                 precompute  
              ---------------- --------------
               representation   True   False 
              ================ ====== =======
                   dense        535M    535M 
                   sparse       108M    n/a  
              ================ ====== =======

[ 52.17%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 53.04%] ··· linear_model.LassoBenchmark.time_fit                            ok
[ 53.04%] ··· ================ ============ =========
              --                     precompute      
              ---------------- ----------------------
               representation      True       False  
              ================ ============ =========
                   dense        1.41±0.02s   1.60±0s 
                   sparse        2.49±0s       n/a   
              ================ ============ =========

[ 53.04%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 53.91%] ··· linear_model.LassoBenchmark.time_predict                        ok
[ 53.91%] ··· ================ ============ ============
              --                       precompute       
              ---------------- -------------------------
               representation      True        False    
              ================ ============ ============
                   dense        48.6±0.3ms   49.2±0.4ms 
                   sparse       2.61±0.2ms      n/a     
              ================ ============ ============

[ 53.91%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 54.78%] ··· linear_model.LassoBenchmark.track_test_score                    ok
[ 54.78%] ··· ================ =================== ====================
              --                              precompute               
              ---------------- ----------------------------------------
               representation          True               False        
              ================ =================== ====================
                   dense        0.927401502428223   0.9274015020526426 
                   sparse       0.948797489688438          n/a         
              ================ =================== ====================

[ 54.78%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 55.65%] ··· linear_model.LassoBenchmark.track_train_score                   ok
[ 55.65%] ··· ================ ==================== ====================
              --                               precompute               
              ---------------- -----------------------------------------
               representation          True                False        
              ================ ==================== ====================
                   dense        0.9276024919080882   0.9276024920078448 
                   sparse       0.9540466797481225          n/a         
              ================ ==================== ====================

[ 55.65%] ···· For parameters: 'sparse', False
               asv: skipped: NotImplementedError()

[ 56.52%] ··· Setting up linear_model:119                                 failed
[ 56.52%] ···· ________________________________________________________________________________
               [Memory] Calling benchmarks.datasets._synth_regression_sparse_dataset...
               _synth_regression_sparse_dataset(n_samples=10000, n_features=100000, density=0.01)
               Traceback (most recent call last):
                 File "/home/ubuntu/miniconda/envs/skl_benchmark/lib/python3.8/site-packages/asv/benchmark.py", line 1435, in <module>
                   main()
                 File "/home/ubuntu/miniconda/envs/skl_benchmark/lib/python3.8/site-packages/asv/benchmark.py", line 1428, in main
                   commands[mode](args)
                 File "/home/ubuntu/miniconda/envs/skl_benchmark/lib/python3.8/site-packages/asv/benchmark.py", line 1136, in main_setup_cache
                   cache = benchmark.do_setup_cache()
                 File "/home/ubuntu/miniconda/envs/skl_benchmark/lib/python3.8/site-packages/asv/benchmark.py", line 570, in do_setup_cache
                   return self._setup_cache()
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/benchmarks/linear_model.py", line 120, in setup_cache
                   super().setup_cache()
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/benchmarks/common.py", line 152, in setup_cache
                   X, _, y, _ = self.make_data(params)
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/benchmarks/linear_model.py", line 128, in make_data
                   data = _synth_regression_sparse_dataset(
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/joblib/memory.py", line 594, in __call__
                   return self._cached_call(args, kwargs)[0]
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/joblib/memory.py", line 537, in _cached_call
                   out, metadata = self.call(*args, **kwargs)
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/joblib/memory.py", line 779, in call
                   output = self.func(*args, **kwargs)
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/benchmarks/datasets.py", line 104, in _synth_regression_sparse_dataset
                   X = sp.random(
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/scipy/sparse/_construct.py", line 887, in random
                   ind = random_state.choice(mn, size=k, replace=False)
                 File "mtrand.pyx", line 991, in numpy.random.mtrand.RandomState.choice
                 File "mtrand.pyx", line 4630, in numpy.random.mtrand.RandomState.permutation
               numpy.core._exceptions.MemoryError: Unable to allocate 7.45 GiB for an array with shape (1000000000,) and data type int64
               
               asv: setup_cache failed (exit status 1)

[ 56.52%] ··· linear_model.LinearRegressionBenchmark.peakmem_fit skipped (setup_cache failed)
[ 57.39%] ··· linear_model.LinearRegressionBenchmark.peakmem_predict skipped (setup_cache failed)
[ 58.26%] ··· linear_model.LinearRegressionBenchmark.time_fit skipped (setup_cache failed)
[ 59.13%] ··· linear_model.LinearRegressionBenchmark.time_predict skipped (setup_cache failed)
[ 60.00%] ··· linear_model.LinearRegressionBenchmark.track_test_score skipped (setup_cache failed)
[ 60.87%] ··· linear_model.LinearRegressionBenchmark.track_train_score skipped (setup_cache failed)
[ 61.74%] ··· Setting up linear_model:28                                      ok
[ 61.74%] ··· ...odel.LogisticRegressionBenchmark.peakmem_fit                 ok
[ 61.74%] ··· ================ ======== ====== ======
              --                            n_jobs   
              ------------------------- -------------
               representation   solver    1      4   
              ================ ======== ====== ======
                   dense        lbfgs    148M   140M 
                   dense         saga    126M   127M 
                   sparse       lbfgs    608M   163M 
                   sparse        saga    149M   149M 
              ================ ======== ====== ======

[ 62.61%] ··· ....LogisticRegressionBenchmark.peakmem_predict                 ok
[ 62.61%] ··· ================ ======== ====== ======
              --                            n_jobs   
              ------------------------- -------------
               representation   solver    1      4   
              ================ ======== ====== ======
                   dense        lbfgs    140M   140M 
                   dense         saga    131M   131M 
                   sparse       lbfgs    143M   143M 
                   sparse        saga    131M   131M 
              ================ ======== ====== ======

[ 63.48%] ··· ...r_model.LogisticRegressionBenchmark.time_fit                 ok
[ 63.48%] ··· ================ ======== ============ ===========
              --                                 n_jobs         
              ------------------------- ------------------------
               representation   solver       1            4     
              ================ ======== ============ ===========
                   dense        lbfgs     713±3ms     1.70±0.2s 
                   dense         saga    5.15±0.04s   5.55±0.5s 
                   sparse       lbfgs    9.81±0.3s    13.4±0.2s 
                   sparse        saga    4.21±0.4s    3.69±0.3s 
              ================ ======== ============ ===========

[ 64.35%] ··· ...del.LogisticRegressionBenchmark.time_predict                 ok
[ 64.35%] ··· ================ ======== ============= =============
              --                                   n_jobs          
              ------------------------- ---------------------------
               representation   solver        1             4      
              ================ ======== ============= =============
                   dense        lbfgs     3.32±0.3ms    3.04±0.2ms 
                   dense         saga    1.75±0.02ms     1.93±0ms  
                   sparse       lbfgs     6.93±0.2ms   6.99±0.05ms 
                   sparse        saga    6.57±0.02ms    5.36±0.6ms 
              ================ ======== ============= =============

[ 65.22%] ··· ...LogisticRegressionBenchmark.track_test_score                 ok
[ 65.22%] ··· ================ ======== ======== ====================
               representation   solver   n_jobs                      
              ---------------- -------- -------- --------------------
                   dense        lbfgs      1      0.7726097125422434 
                   dense        lbfgs      4      0.7726097125422434 
                   dense         saga      1      0.7795862469757763 
                   dense         saga      4      0.7795862469757763 
                   sparse       lbfgs      1      0.7374230817342273 
                   sparse       lbfgs      4      0.7374230817342273 
                   sparse        saga      1      0.5765140080078162 
                   sparse        saga      4      0.5765140080078162 
              ================ ======== ======== ====================

[ 66.09%] ··· ...ogisticRegressionBenchmark.track_train_score                 ok
[ 66.09%] ··· ================ ======== ======== ====================
               representation   solver   n_jobs                      
              ---------------- -------- -------- --------------------
                   dense        lbfgs      1      0.7826631031195346 
                   dense        lbfgs      4      0.7826631031195346 
                   dense         saga      1      0.7967778141859048 
                   dense         saga      4      0.7967778141859048 
                   sparse       lbfgs      1      0.969018004684019  
                   sparse       lbfgs      4      0.969018004684019  
                   sparse        saga      1      0.6908414295256007 
                   sparse        saga      4      0.6908414295256007 
              ================ ======== ======== ====================

[ 66.96%] ··· Setting up linear_model:78                                  failed
[ 66.96%] ···· ________________________________________________________________________________
               [Memory] Calling benchmarks.datasets._synth_regression_dataset...
               _synth_regression_dataset(n_samples=500000, n_features=100)
               _________________________________________synth_regression_dataset - 6.2s, 0.1min
               ________________________________________________________________________________
               [Memory] Calling benchmarks.datasets._synth_regression_sparse_dataset...
               _synth_regression_sparse_dataset(n_samples=100000, n_features=10000, density=0.005)
               Traceback (most recent call last):
                 File "/home/ubuntu/miniconda/envs/skl_benchmark/lib/python3.8/site-packages/asv/benchmark.py", line 1435, in <module>
                   main()
                 File "/home/ubuntu/miniconda/envs/skl_benchmark/lib/python3.8/site-packages/asv/benchmark.py", line 1428, in main
                   commands[mode](args)
                 File "/home/ubuntu/miniconda/envs/skl_benchmark/lib/python3.8/site-packages/asv/benchmark.py", line 1136, in main_setup_cache
                   cache = benchmark.do_setup_cache()
                 File "/home/ubuntu/miniconda/envs/skl_benchmark/lib/python3.8/site-packages/asv/benchmark.py", line 570, in do_setup_cache
                   return self._setup_cache()
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/benchmarks/linear_model.py", line 79, in setup_cache
                   super().setup_cache()
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/benchmarks/common.py", line 152, in setup_cache
                   X, _, y, _ = self.make_data(params)
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/benchmarks/linear_model.py", line 87, in make_data
                   data = _synth_regression_sparse_dataset(
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/joblib/memory.py", line 594, in __call__
                   return self._cached_call(args, kwargs)[0]
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/joblib/memory.py", line 537, in _cached_call
                   out, metadata = self.call(*args, **kwargs)
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/joblib/memory.py", line 779, in call
                   output = self.func(*args, **kwargs)
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/benchmarks/datasets.py", line 104, in _synth_regression_sparse_dataset
                   X = sp.random(
                 File "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/scipy/sparse/_construct.py", line 887, in random
                   ind = random_state.choice(mn, size=k, replace=False)
                 File "mtrand.pyx", line 991, in numpy.random.mtrand.RandomState.choice
                 File "mtrand.pyx", line 4630, in numpy.random.mtrand.RandomState.permutation
               numpy.core._exceptions.MemoryError: Unable to allocate 7.45 GiB for an array with shape (1000000000,) and data type int64
               
               asv: setup_cache failed (exit status 1)

[ 66.96%] ··· linear_model.RidgeBenchmark.peakmem_fit skipped (setup_cache failed)
[ 67.83%] ··· linear_model.RidgeBenchmark.peakmem_predict skipped (setup_cache failed)
[ 68.70%] ··· linear_model.RidgeBenchmark.time_fit skipped (setup_cache failed)
[ 69.57%] ··· linear_model.RidgeBenchmark.time_predict skipped (setup_cache failed)
[ 70.43%] ··· linear_model.RidgeBenchmark.track_test_score skipped (setup_cache failed)
[ 71.30%] ··· linear_model.RidgeBenchmark.track_train_score skipped (setup_cache failed)
[ 72.17%] ··· Setting up linear_model:151                                     ok
[ 72.17%] ··· linear_model.SGDRegressorBenchmark.peakmem_fit                  ok
[ 72.17%] ··· ================ ======
               representation        
              ---------------- ------
                   dense        203M 
                   sparse       133M 
              ================ ======

[ 73.04%] ··· ..._model.SGDRegressorBenchmark.peakmem_predict                 ok
[ 73.04%] ··· ================ ======
               representation        
              ---------------- ------
                   dense        206M 
                   sparse       129M 
              ================ ======

[ 73.91%] ··· linear_model.SGDRegressorBenchmark.time_fit                     ok
[ 73.91%] ··· ================ ============
               representation              
              ---------------- ------------
                   dense         4.78±0s   
                   sparse       11.4±0.09s 
              ================ ============

[ 74.78%] ··· linear_model.SGDRegressorBenchmark.time_predict                 ok
[ 74.78%] ··· ================ =============
               representation               
              ---------------- -------------
                   dense         10.8±0.7ms 
                   sparse       2.18±0.01ms 
              ================ =============

[ 75.65%] ··· ...model.SGDRegressorBenchmark.track_test_score                 ok
[ 75.65%] ··· ================ ====================
               representation                      
              ---------------- --------------------
                   dense        0.9635760774984229 
                   sparse       0.9622303553790755 
              ================ ====================

[ 76.52%] ··· ...odel.SGDRegressorBenchmark.track_train_score                 ok
[ 76.52%] ··· ================ ====================
               representation                      
              ---------------- --------------------
                   dense        0.964165001382414  
                   sparse       0.9616902042022277 
              ================ ====================

[ 77.39%] ··· Setting up manifold:15                                          ok
[ 77.39%] ··· manifold.TSNEBenchmark.peakmem_fit                              ok
[ 77.39%] ··· ============ ======
                 method          
              ------------ ------
                 exact      142M 
               barnes_hut   149M 
              ============ ======

[ 78.26%] ··· manifold.TSNEBenchmark.time_fit                                 ok
[ 78.26%] ··· ============ ============
                 method                
              ------------ ------------
                 exact      10.8±0.2s  
               barnes_hut   3.28±0.01s 
              ============ ============

[ 79.13%] ··· manifold.TSNEBenchmark.track_test_score                         ok
[ 79.13%] ··· ============ ====================
                 method                        
              ------------ --------------------
                 exact      0.3234750877677249 
               barnes_hut   0.7250226736068726 
              ============ ====================

[ 80.00%] ··· manifold.TSNEBenchmark.track_train_score                        ok
[ 80.00%] ··· ============ ====================
                 method                        
              ------------ --------------------
                 exact      0.3234750877677249 
               barnes_hut   0.7250226736068726 
              ============ ====================

[ 80.87%] ··· ...istancesBenchmark.peakmem_pairwise_distances                 ok
[ 80.87%] ··· ================ ============= ======= =======
              --                                  n_jobs    
              ------------------------------ ---------------
               representation      metric       1       4   
              ================ ============= ======= =======
                   dense           cosine      697M   1.08G 
                   dense         euclidean     799M   1.04G 
                   dense         manhattan     297M    378M 
                   dense        correlation    290M    492M 
                   sparse          cosine     1.46G   1.27G 
                   sparse        euclidean     614M    928M 
                   sparse        manhattan     229M    276M 
                   sparse       correlation    n/a     n/a  
              ================ ============= ======= =======

[ 80.87%] ···· For parameters: 'dense', 'cosine', 1
               ________________________________________________________________________________
               [Memory] Calling benchmarks.datasets._random_dataset...
               _random_dataset(n_samples=12000, representation='dense')
               ___________________________________________________random_dataset - 0.2s, 0.0min
               
               For parameters: 'dense', 'manhattan', 1
               ________________________________________________________________________________
               [Memory] Calling benchmarks.datasets._random_dataset...
               _random_dataset(n_samples=4000, representation='dense')
               ___________________________________________________random_dataset - 0.1s, 0.0min
               
               For parameters: 'sparse', 'cosine', 1
               ________________________________________________________________________________
               [Memory] Calling benchmarks.datasets._random_dataset...
               _random_dataset(n_samples=12000, representation='sparse')
               ___________________________________________________random_dataset - 0.9s, 0.0min
               
               For parameters: 'sparse', 'manhattan', 1
               ________________________________________________________________________________
               [Memory] Calling benchmarks.datasets._random_dataset...
               _random_dataset(n_samples=4000, representation='sparse')
               ___________________________________________________random_dataset - 0.1s, 0.0min
               
               For parameters: 'sparse', 'correlation', 1
               asv: skipped: NotImplementedError()
               
               For parameters: 'sparse', 'correlation', 4
               asv: skipped: NotImplementedError()

[ 81.74%] ··· ...seDistancesBenchmark.time_pairwise_distances                 ok
[ 81.74%] ··· ================ ============= ============ ============
              --                                       n_jobs         
              ------------------------------ -------------------------
               representation      metric         1            4      
              ================ ============= ============ ============
                   dense           cosine     1.13±0.01s   1.12±0.04s 
                   dense         euclidean    1.61±0.01s   2.68±0.04s 
                   dense         manhattan    7.43±0.1s    2.55±0.04s 
                   dense        correlation   3.71±0.01s   2.62±0.08s 
                   sparse          cosine     3.76±0.2s    2.58±0.2s  
                   sparse        euclidean    3.45±0.05s   5.60±0.04s 
                   sparse        manhattan     1.00±0s     1.32±0.03s 
                   sparse       correlation      n/a          n/a     
              ================ ============= ============ ============

[ 81.74%] ···· For parameters: 'sparse', 'correlation', 1
               asv: skipped: NotImplementedError()
               
               For parameters: 'sparse', 'correlation', 4
               asv: skipped: NotImplementedError()

[ 82.61%] ··· ...on.CrossValidationBenchmark.peakmem_crossval                 ok
[ 82.61%] ··· ======== ======
               n_jobs        
              -------- ------
                 1      230M 
                 4      160M 
              ======== ======

[ 82.61%] ···· For parameters: 1
               ________________________________________________________________________________
               [Memory] Calling benchmarks.datasets._synth_classification_dataset...
               _synth_classification_dataset(n_samples=50000, n_features=100)
               _____________________________________synth_classification_dataset - 0.9s, 0.0min

[ 83.48%] ··· ...ction.CrossValidationBenchmark.time_crossval                 ok
[ 83.48%] ··· ======== ============
               n_jobs              
              -------- ------------
                 1      1.57±0.05m 
                 4      24.4±0.3s  
              ======== ============

[ 84.35%] ··· ...tion.CrossValidationBenchmark.track_crossval                 ok
[ 84.35%] ··· ======== ====================
               n_jobs                      
              -------- --------------------
                 1      0.9001555555555555 
                 4      0.9001555555555555 
              ======== ====================

[ 85.22%] ··· Setting up model_selection:51                                   ok
[ 85.22%] ··· model_selection.GridSearchBenchmark.peakmem_fit                 ok
[ 85.22%] ··· ======== ======
               n_jobs        
              -------- ------
                 1      136M 
                 4      132M 
              ======== ======

[ 86.09%] ··· ...election.GridSearchBenchmark.peakmem_predict                 ok
[ 86.09%] ··· ======== ======
               n_jobs        
              -------- ------
                 1      127M 
                 4      127M 
              ======== ======

[ 86.96%] ··· model_selection.GridSearchBenchmark.time_fit                    ok
[ 86.96%] ··· ======== ============
               n_jobs              
              -------- ------------
                 1      9.06±0.2m  
                 4      2.51±0.01m 
              ======== ============

[ 87.83%] ··· ...l_selection.GridSearchBenchmark.time_predict                 ok
[ 87.83%] ··· ======== ============
               n_jobs              
              -------- ------------
                 1      77.2±0.1ms 
                 4      77.2±0.1ms 
              ======== ============

[ 88.70%] ··· ...lection.GridSearchBenchmark.track_test_score                 ok
[ 88.70%] ··· ======== ====================
               n_jobs                      
              -------- --------------------
                 1      0.8678060899936387 
                 4      0.8678060899936387 
              ======== ====================

[ 89.57%] ··· ...ection.GridSearchBenchmark.track_train_score                 ok
[ 89.57%] ··· ======== ====================
               n_jobs                      
              -------- --------------------
                 1      0.9966662088870577 
                 4      0.9966662088870577 
              ======== ====================

[ 90.43%] ··· Setting up neighbors:16                                         ok
[ 90.43%] ··· ...rs.KNeighborsClassifierBenchmark.peakmem_fit                 ok
[ 90.43%] ··· =========== ========= ========= ========== ==========
              --                      dimension / n_jobs           
              ----------- -----------------------------------------
               algorithm   low / 1   low / 4   high / 1   high / 4 
              =========== ========= ========= ========== ==========
                 brute       120M      120M      124M       124M   
                kd_tree      122M      122M      131M       131M   
               ball_tree     122M      122M      131M       131M   
              =========== ========= ========= ========== ==========

[ 91.30%] ··· ...NeighborsClassifierBenchmark.peakmem_predict                 ok
[ 91.30%] ··· =========== ========= ========= ========== ==========
              --                      dimension / n_jobs           
              ----------- -----------------------------------------
               algorithm   low / 1   low / 4   high / 1   high / 4 
              =========== ========= ========= ========== ==========
                 brute       136M      136M      142M       142M   
                kd_tree      124M      126M      134M       136M   
               ball_tree     124M      126M      134M       136M   
              =========== ========= ========= ========== ==========

[ 92.17%] ··· ...hbors.KNeighborsClassifierBenchmark.time_fit                 ok
[ 92.17%] ··· =========== =========== ============= =============
              --                                 n_jobs          
              ----------------------- ---------------------------
               algorithm   dimension        1             4      
              =========== =========== ============= =============
                 brute        low      1.11±0.01ms   1.55±0.01ms 
                 brute        high      1.77±0.2ms   1.28±0.01ms 
                kd_tree       low      11.5±0.06ms     16.6±2ms  
                kd_tree       high      53.9±0.5ms     47.9±9ms  
               ball_tree      low      12.8±0.05ms   12.7±0.02ms 
               ball_tree      high       35.4±7ms      39.1±5ms  
              =========== =========== ============= =============

[ 93.04%] ··· ...s.KNeighborsClassifierBenchmark.time_predict                 ok
[ 93.04%] ··· =========== =========== ============ ============
              --                                n_jobs         
              ----------------------- -------------------------
               algorithm   dimension       1            4      
              =========== =========== ============ ============
                 brute        low       66.2±2ms    66.0±0.3ms 
                 brute        high      105±3ms      105±3ms   
                kd_tree       low       932±10ms    2.08±0.3s  
                kd_tree       high     7.84±0.03s   8.21±0.7s  
               ball_tree      low      1.84±0.02s   4.55±0.4s  
               ball_tree      high     7.44±0.06s   10.1±0.7s  
              =========== =========== ============ ============

[ 93.91%] ··· ...eighborsClassifierBenchmark.track_test_score                 ok
[ 93.91%] ··· =========== =========== ======== ====================
               algorithm   dimension   n_jobs                      
              ----------- ----------- -------- --------------------
                 brute        low        1      0.4174646735908274 
                 brute        low        4      0.4174646735908274 
                 brute        high       1      0.6439865182459598 
                 brute        high       4      0.6439865182459598 
                kd_tree       low        1      0.4174646735908274 
                kd_tree       low        4      0.4174646735908274 
                kd_tree       high       1      0.6439865182459598 
                kd_tree       high       4      0.6439865182459598 
               ball_tree      low        1      0.4174646735908274 
               ball_tree      low        4      0.4174646735908274 
               ball_tree      high       1      0.6439865182459598 
               ball_tree      high       4      0.6439865182459598 
              =========== =========== ======== ====================

[ 94.78%] ··· ...ighborsClassifierBenchmark.track_train_score                 ok
[ 94.78%] ··· =========== =========== ======== ====================
               algorithm   dimension   n_jobs                      
              ----------- ----------- -------- --------------------
                 brute        low        1      0.6266777532505527 
                 brute        low        4      0.6266777532505527 
                 brute        high       1      0.7911714449902014 
                 brute        high       4      0.7911714449902014 
                kd_tree       low        1      0.6266777532505527 
                kd_tree       low        4      0.6266777532505527 
                kd_tree       high       1      0.7911714449902014 
                kd_tree       high       4      0.7911714449902014 
               ball_tree      low        1      0.6266777532505527 
               ball_tree      low        4      0.6266777532505527 
               ball_tree      high       1      0.7911714449902014 
               ball_tree      high       4      0.7911714449902014 
              =========== =========== ======== ====================

[ 95.65%] ··· Setting up svm:14                                               ok
[ 95.65%] ··· svm.SVCBenchmark.peakmem_fit                                    ok
[ 95.65%] ··· ========= ======
                kernel        
              --------- ------
                linear   319M 
                 poly    319M 
                 rbf     319M 
               sigmoid   319M 
              ========= ======

[ 95.65%] ···· For parameters: 'linear'
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               
               For parameters: 'poly'
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               
               For parameters: 'rbf'
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               
               For parameters: 'sigmoid'
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(

[ 96.52%] ··· svm.SVCBenchmark.peakmem_predict                                ok
[ 96.52%] ··· ========= ======
                kernel        
              --------- ------
                linear   252M 
                 poly    252M 
                 rbf     252M 
               sigmoid   252M 
              ========= ======

[ 97.39%] ··· svm.SVCBenchmark.time_fit                                       ok
[ 97.39%] ··· ========= =========
                kernel           
              --------- ---------
                linear   903±2ms 
                 poly    926±3ms 
                 rbf     859±3ms 
               sigmoid   907±3ms 
              ========= =========

[ 97.39%] ···· For parameters: 'linear'
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               
               For parameters: 'poly'
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               
               For parameters: 'rbf'
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               
               For parameters: 'sigmoid'
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(
               /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/python3.8/site-packages/sklearn/svm/_base.py:299: ConvergenceWarning: Solver terminated early (max_iter=100).  Consider pre-processing your data with StandardScaler or MinMaxScaler.
                 warnings.warn(

[ 98.26%] ··· svm.SVCBenchmark.time_predict                                   ok
[ 98.26%] ··· ========= ============
                kernel              
              --------- ------------
                linear    737±2ms   
                 poly     723±4ms   
                 rbf     3.53±0.03s 
               sigmoid    683±3ms   
              ========= ============

[ 99.13%] ··· svm.SVCBenchmark.track_test_score                               ok
[ 99.13%] ··· ========= ====================
                kernel                      
              --------- --------------------
                linear   0.5899537620849096 
                 poly           0.5         
                 rbf     0.564312736443884  
               sigmoid   0.5710382513661202 
              ========= ====================

[100.00%] ··· svm.SVCBenchmark.track_train_score                              ok
[100.00%] ··· ========= ====================
                kernel                      
              --------- --------------------
                linear   0.7373393801965231 
                 poly    0.6089324618736384 
                 rbf     0.7382063936685785 
               sigmoid   0.741296518607443  
              ========= ====================



***** Publish *****

[ 11.11%] · Loading machine info
[ 22.22%] · Getting params, commits, tags and branches
[ 33.33%] · Loading results
[ 33.33%] ·· Couldn't find 0fb307bf in branches (main)
[ 44.44%] · Detecting steps
[ 55.56%] · Generating graphs
[ 66.67%] · Generating output for SummaryGrid
[ 77.78%] · Generating output for SummaryList
[ 88.89%] · Generating output for Regressions
[100.00%] · Writing index


***** Dependencies *****

# packages in environment at /home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99:
#
# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                        main  
_openmp_mutex             5.1                       1_gnu  
appdirs                   1.4.4              pyhd3eb1b0_0  
blas                      1.0                         mkl  
bottleneck                1.3.5            py38h7deecbd_0  
brotlipy                  0.7.0           py38h27cfd23_1003  
ca-certificates           2023.01.10           h06a4308_0  
certifi                   2022.12.7        py38h06a4308_0  
cffi                      1.15.1           py38h5eee18b_3  
charset-normalizer        2.0.4              pyhd3eb1b0_0  
cryptography              39.0.1           py38h9ce1e76_0  
cython                    0.29.33          py38h6a678d5_0  
idna                      3.4              py38h06a4308_0  
intel-openmp              2021.4.0          h06a4308_3561  
joblib                    1.1.1            py38h06a4308_0  
ld_impl_linux-64          2.38                 h1181459_1  
libffi                    3.4.2                h6a678d5_6  
libgcc-ng                 11.2.0               h1234567_1  
libgfortran-ng            11.2.0               h00389a5_1  
libgfortran5              11.2.0               h1234567_1  
libgomp                   11.2.0               h1234567_1  
libstdcxx-ng              11.2.0               h1234567_1  
mkl                       2021.4.0           h06a4308_640  
mkl-service               2.4.0            py38h7f8727e_0  
mkl_fft                   1.3.1            py38hd3c417c_0  
mkl_random                1.2.2            py38h51133e4_0  
ncurses                   6.4                  h6a678d5_0  
numexpr                   2.8.4            py38he184ba9_0  
numpy                     1.23.5           py38h14f4228_0  
numpy-base                1.23.5           py38h31eccc5_0  
openssl                   1.1.1t               h7f8727e_0  
packaging                 23.0             py38h06a4308_0  
pandas                    1.5.3            py38h417a72b_0  
pip                       23.0.1           py38h06a4308_0  
pooch                     1.4.0              pyhd3eb1b0_0  
pycparser                 2.21               pyhd3eb1b0_0  
pyopenssl                 23.0.0           py38h06a4308_0  
pysocks                   1.7.1            py38h06a4308_0  
python                    3.8.16               h7a1cb2a_3  
python-dateutil           2.8.2              pyhd3eb1b0_0  
pytz                      2022.7           py38h06a4308_0  
readline                  8.2                  h5eee18b_0  
requests                  2.28.1           py38h06a4308_1  
scikit-learn              1.3.dev0                 pypi_0    pypi
scipy                     1.10.0           py38h14f4228_1  
setuptools                65.6.3           py38h06a4308_0  
six                       1.16.0             pyhd3eb1b0_1  
sqlite                    3.41.1               h5eee18b_0  
threadpoolctl             2.2.0              pyh0d69192_0  
tk                        8.6.12               h1ccaba5_0  
urllib3                   1.26.14          py38h06a4308_0  
wheel                     0.38.4           py38h06a4308_0  
xz                        5.2.10               h5eee18b_1  
zlib                      1.2.13               h5eee18b_0  


***** Threadpool info *****

[
  {
    "filepath": "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/libgomp.so.1.0.0",
    "prefix": "libgomp",
    "user_api": "openmp",
    "internal_api": "openmp",
    "version": null,
    "num_threads": 8
  },
  {
    "filepath": "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/libmkl_rt.so.1",
    "prefix": "libmkl_rt",
    "user_api": "blas",
    "internal_api": "mkl",
    "version": "2021.4-Product",
    "num_threads": 8,
    "threading_layer": "intel"
  },
  {
    "filepath": "/home/ubuntu/scikit-learn/asv_benchmarks/env/90ed7782ee9013f1c8d13fdff8043a99/lib/libiomp5.so",
    "prefix": "libiomp",
    "user_api": "openmp",
    "internal_api": "openmp",
    "version": null,
    "num_threads": 8
  }
]


***** System info *****

Architecture:        x86_64
CPU op-mode(s):      32-bit, 64-bit
Byte Order:          Little Endian
CPU(s):              8
On-line CPU(s) list: 0-7
Thread(s) per core:  1
Core(s) per socket:  1
Socket(s):           8
NUMA node(s):        1
Vendor ID:           GenuineIntel
CPU family:          6
Model:               60
Model name:          Intel Core Processor (Haswell, no TSX)
Stepping:            1
CPU MHz:             2294.682
BogoMIPS:            4589.36
Hypervisor vendor:   KVM
Virtualization type: full
L1d cache:           32K
L1i cache:           32K
L2 cache:            4096K
NUMA node0 CPU(s):   0-7
Flags:               fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl cpuid pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm invpcid_single pti fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid xsaveopt arat
MemTotal:       16424676 kB