(base) onyxia@jupyter-python-gpu-228609-0:~/work/LSVI/LSVI/experiments/logisticRegression/pima_logistic_regression$ command time --verbose python time.py
INFO:root:Function       <function time_gaussian at 0x7f1bb4100cc0>
Args           ()
Kwargs         {}
Runs           5
Workers        1
Average Time   1.5805183887481689s
Median Time    0.9638471603393555s
Min Time       0.9459934234619141s
Max Time       4.068429231643677s
Std Deviation  1.3908315129742197s
Total Time     7.902591943740845s

INFO:root:Function       <function time_gaussian_Anon_seq1 at 0x7f18d021f880> # N = 10^4
Args           ()
Kwargs         {}
Runs           5
Workers        1
Average Time   2.4263389110565186s
Median Time    2.000624656677246s
Min Time       1.9830098152160645s
Max Time       4.107008695602417s
Std Deviation  0.9398359276240136s
Total Time     12.131694555282593s

INFO:root:Function       <function time_gaussian_Anon_seq2 at 0x7f18d02951c0> # N = 10^4
Args           ()
Kwargs         {}
Runs           5
Workers        1
Average Time   1.7724379062652589s
Median Time    1.7380681037902832s
Min Time       1.6729516983032227s
Max Time       1.8952629566192627s
Std Deviation  0.09887113592552452s
Total Time     8.862189531326294s

point={'beta': array([0., 0., 0., 0., 0., 0., 0., 0., 0.])}

No problems found
MAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0:00:02 logp = -386.04, ||grad|| = 0.017674
MAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0:00:02 logp = -386.04, ||grad|| = 0.017674
Fitting: ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00 Average Loss = 393.02
Finished [100%]: Average Loss = 393.02
INFO:pymc.variational.inference:Finished [100%]: Average Loss = 393.02
point={'beta': array([0., 0., 0., 0., 0., 0., 0., 0., 0.])}

No problems found
MAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0:00:02 logp = -386.04, ||grad|| = 0.017674
MAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0:00:02 logp = -386.04, ||grad|| = 0.017674
Fitting: ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00 Average Loss = 393.04
Finished [100%]: Average Loss = 393.04
INFO:pymc.variational.inference:Finished [100%]: Average Loss = 393.04
point={'beta': array([0., 0., 0., 0., 0., 0., 0., 0., 0.])}

No problems found
MAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0:00:02 logp = -386.04, ||grad|| = 0.017674
MAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0:00:02 logp = -386.04, ||grad|| = 0.017674
Fitting: ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00 Average Loss = 393.02
Finished [100%]: Average Loss = 393.02
INFO:pymc.variational.inference:Finished [100%]: Average Loss = 393.02
point={'beta': array([0., 0., 0., 0., 0., 0., 0., 0., 0.])}

No problems found
MAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0:00:02 logp = -386.04, ||grad|| = 0.017674
MAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0:00:02 logp = -386.04, ||grad|| = 0.017674
Fitting: ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00 Average Loss = 393.03
Finished [100%]: Average Loss = 393.03
INFO:pymc.variational.inference:Finished [100%]: Average Loss = 393.03
point={'beta': array([0., 0., 0., 0., 0., 0., 0., 0., 0.])}

No problems found
MAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0:00:02 logp = -386.04, ||grad|| = 0.017674
MAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% 0:00:02 logp = -386.04, ||grad|| = 0.017674
Fitting: ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00 Average Loss = 393.04
Finished [100%]: Average Loss = 393.04
INFO:pymc.variational.inference:Finished [100%]: Average Loss = 393.04
INFO:root:Function       <function time_gaussian_ADVI at 0x7f18d02b4540>
Args           ()
Kwargs         {}
Runs           5
Workers        1
Average Time   5.854104852676391s
Median Time    5.773375988006592s
Min Time       5.496805191040039s
Max Time       6.436511754989624s
Std Deviation  0.348248737652404s
Total Time     29.270524263381958s

        Command being timed: "python time.py"
        User time (seconds): 86.25
        System time (seconds): 25.32
        Percent of CPU this job got: 171%
        Elapsed (wall clock) time (h:mm:ss or m:ss): 1:05.20
        Average shared text size (kbytes): 0
        Average unshared data size (kbytes): 0
        Average stack size (kbytes): 0
        Average total size (kbytes): 0
        Maximum resident set size (kbytes): 1507492
        Average resident set size (kbytes): 0
        Major (requiring I/O) page faults: 0
        Minor (reclaiming a frame) page faults: 1044274
        Voluntary context switches: 568782
        Involuntary context switches: 1868
        Swaps: 0
        File system inputs: 0
        File system outputs: 75760
        Socket messages sent: 0
        Socket messages received: 0
        Signals delivered: 0
        Page size (bytes): 4096
        Exit status: 0


INFO:root:Function       <function time_heuristic_gaussianMeanField_Anon_u10_fixed1em3 at 0x7fb6b01efa60>
Args           ()
Kwargs         {}
Runs           5
Workers        1
Average Time   101.93914608955383s
Median Time    101.14689540863037s
Min Time       101.04589366912842s
Max Time       104.73575472831726s
Std Deviation  1.5798447448066881s
Total Time     509.69573044776917s

        Command being timed: "python time.py"
        User time (seconds): 519.43
        System time (seconds): 11.64
        Percent of CPU this job got: 103%
        Elapsed (wall clock) time (h:mm:ss or m:ss): 8:33.94
        Average shared text size (kbytes): 0
        Average unshared data size (kbytes): 0
        Average stack size (kbytes): 0
        Average total size (kbytes): 0
        Maximum resident set size (kbytes): 2362684
        Average resident set size (kbytes): 0
        Major (requiring I/O) page faults: 0
        Minor (reclaiming a frame) page faults: 1124839
        Voluntary context switches: 132871
        Involuntary context switches: 2792
        Swaps: 0
        File system inputs: 0
        File system outputs: 63152
        Socket messages sent: 0
        Socket messages received: 0
        Signals delivered: 0
        Page size (bytes): 4096
        Exit status: 0

ime.py
INFO:root:Function       <function time_gaussianMeanField_bj at 0x7f433033dee0>
Args           ()
Kwargs         {}
Runs           5
Workers        1
Average Time   99.11265463829041s
Median Time    98.52845239639282s
Min Time       98.20894074440002s
Max Time       101.25234031677246s
Std Deviation  1.2437057356432066s
Total Time     495.563273191452s

        Command being timed: "python time.py"
        User time (seconds): 123.12
        System time (seconds): 20.17
        Percent of CPU this job got: 28%
        Elapsed (wall clock) time (h:mm:ss or m:ss): 8:19.57
        Average shared text size (kbytes): 0
        Average unshared data size (kbytes): 0
        Average stack size (kbytes): 0
        Average total size (kbytes): 0
        Maximum resident set size (kbytes): 3345064
        Average resident set size (kbytes): 0
        Major (requiring I/O) page faults: 0
        Minor (reclaiming a frame) page faults: 4195286
        Voluntary context switches: 133398
        Involuntary context switches: 1137
        Swaps: 0
        File system inputs: 0
        File system outputs: 62648
        Socket messages sent: 0
        Socket messages received: 0
        Signals delivered: 0

(lsvi) onyxia@jupyter-python-gpu-228609-0:~/work/LSVI/LSVI/experiments/logisticRegression/pima_logistic_regression$ python time.py
INFO:root:Function       <function time_gaussian_Anon_seq1 at 0x7efef85f7920>
Args           ()
Kwargs         {}
Runs           5
Workers        1
Average Time   4.344598913192749s
Median Time    3.6004884243011475s
Min Time       3.5697667598724365s
Max Time       7.3354246616363525s
Std Deviation  1.6720416939443337s
Total Time     21.722994565963745s

INFO:root:Function       <function time_gaussian_Anon_seq2 at 0x7efef8475260>
Args           ()
Kwargs         {}
Runs           5
Workers        1
Average Time   3.4051965713500976s
Median Time    3.3625986576080322s
Min Time       3.354137420654297s
Max Time       3.581826686859131s
Std Deviation  0.09889750800421679s
Total Time     17.02598285675049s
