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Posted to dev@madlib.apache.org by GitBox <gi...@apache.org> on 2021/01/22 00:32:28 UTC

[GitHub] [madlib] fmcquillan99 commented on pull request #531: DL: print timing for evaluate operation in fit multiple

fmcquillan99 commented on pull request #531:
URL: https://github.com/apache/madlib/pull/531#issuecomment-765030529


   ```
   madlib=# SELECT madlib.madlib_keras_fit_multiple_model('iris_train_packed',    -- source_table
   madlib(#                                               'iris_multi_model',     -- model_output_table
   madlib(#                                               'mst_table',            -- model_selection_table
   madlib(#                                                10,                     -- num_iterations
   madlib(#                                                FALSE,                 -- use gpus
   madlib(#                                               'iris_test_packed',     -- validation dataset
   madlib(#                                                1,                     -- metrics compute frequency
   madlib(#                                                FALSE,                 -- warm start
   madlib(#                                               'Sophie L.',            -- name
   madlib(#                                               'Model selection for iris dataset'  -- description
   madlib(#                                              );
   INFO:  
   	Time for training in iteration 1: 5.08531904221 sec
   DETAIL:  
   	Training set after iteration 1:
   	mst_key=1: metric=0.658333361149, loss=1.1474006176
   	mst_key=3: metric=0.10000000149, loss=1.38732385635
   	mst_key=2: metric=0.333333343267, loss=1.0933380127
   	mst_key=4: metric=0.533333361149, loss=1.7163516283
   	Time for evaluating training dataset in iteration 1: 1.03906393051
   	
   	Validation set after iteration 1:
   	mst_key=1: metric=0.699999988079, loss=1.10724759102
   	mst_key=3: metric=0.166666671634, loss=1.39472186565
   	mst_key=2: metric=0.333333343267, loss=1.08243787289
   	mst_key=4: metric=0.533333361149, loss=1.8540776968
   	Time for evaluating validation dataset in iteration 1: 1.13996315002
   CONTEXT:  PL/Python function "madlib_keras_fit_multiple_model"
   INFO:  
   	Time for training in iteration 2: 3.52112603188 sec
   DETAIL:  
   	Training set after iteration 2:
   	mst_key=1: metric=0.658333361149, loss=1.14587247372
   	mst_key=3: metric=0.108333334327, loss=1.32700014114
   	mst_key=2: metric=0.333333343267, loss=1.08806085587
   	mst_key=4: metric=0.625, loss=1.65616095066
   	Time for evaluating training dataset in iteration 2: 1.04296994209
   	
   	Validation set after iteration 2:
   	mst_key=1: metric=0.699999988079, loss=1.10603606701
   	mst_key=3: metric=0.166666671634, loss=1.3331912756
   	mst_key=2: metric=0.333333343267, loss=1.07862055302
   	mst_key=4: metric=0.566666662693, loss=1.79157197475
   	Time for evaluating validation dataset in iteration 2: 1.17975687981
   etc.
   ```
   
   ```
   madlib=# SELECT madlib.madlib_keras_fit_multiple_model('iris_train_packed',    -- source_table
   madlib(#                                               'iris_multi_model',     -- model_output_table
   madlib(#                                               'mst_table',            -- model_selection_table
   madlib(#                                                10,                     -- num_iterations
   madlib(#                                                FALSE,                 -- use gpus
   madlib(#                                               'iris_test_packed',     -- validation dataset
   madlib(#                                                3,                     -- metrics compute frequency
   madlib(#                                                FALSE,                 -- warm start
   madlib(#                                               'Sophie L.',            -- name
   madlib(#                                               'Model selection for iris dataset'  -- description
   madlib(#                                              );
   INFO:  
   	Time for training in iteration 1: 5.23196315765 sec
   CONTEXT:  PL/Python function "madlib_keras_fit_multiple_model"
   INFO:  
   	Time for training in iteration 2: 3.06432795525 sec
   CONTEXT:  PL/Python function "madlib_keras_fit_multiple_model"
   INFO:  
   	Time for training in iteration 3: 3.11480093002 sec
   DETAIL:  
   	Training set after iteration 3:
   	mst_key=1: metric=0.341666668653, loss=1.00513792038
   	mst_key=3: metric=0.341666668653, loss=1.14255702496
   	mst_key=2: metric=0.333333343267, loss=1.30739760399
   	mst_key=4: metric=0.341666668653, loss=1.01052212715
   	Time for evaluating training dataset in iteration 3: 1.07409715652
   	
   	Validation set after iteration 3:
   	mst_key=1: metric=0.300000011921, loss=1.03619933128
   	mst_key=3: metric=0.300000011921, loss=1.15146791935
   	mst_key=2: metric=0.333333343267, loss=1.27005898952
   	mst_key=4: metric=0.300000011921, loss=1.08076310158
   	Time for evaluating validation dataset in iteration 3: 1.44217610359
   etc
   ```
   
   ```
   madlib=# SELECT madlib.madlib_keras_fit_multiple_model('iris_train_packed',    -- source_table
   madlib(#                                               'iris_multi_model',     -- model_output_table
   madlib(#                                               'mst_table',            -- model_selection_table
   madlib(#                                               5,                     -- num_iterations
   madlib(#                                               FALSE                   -- use gpus
   madlib(#                                              );
   INFO:  
   	Time for training in iteration 1: 3.21357607841 sec
   CONTEXT:  PL/Python function "madlib_keras_fit_multiple_model"
   INFO:  
   	Time for training in iteration 2: 3.24296498299 sec
   CONTEXT:  PL/Python function "madlib_keras_fit_multiple_model"
   INFO:  
   	Time for training in iteration 3: 3.2322010994 sec
   CONTEXT:  PL/Python function "madlib_keras_fit_multiple_model"
   INFO:  
   	Time for training in iteration 4: 3.33785796165 sec
   CONTEXT:  PL/Python function "madlib_keras_fit_multiple_model"
   INFO:  
   	Time for training in iteration 5: 3.1472928524 sec
   DETAIL:  
   	Training set after iteration 5:
   	mst_key=1: metric=0.675000011921, loss=1.01427876949
   	mst_key=3: metric=0.341666668653, loss=0.958754897118
   	mst_key=2: metric=0.324999988079, loss=1.13000130653
   	mst_key=4: metric=0.341666668653, loss=1.0127518177
   	Time for evaluating training dataset in iteration 5: 1.03426170349
   CONTEXT:  PL/Python function "madlib_keras_fit_multiple_model"
    madlib_keras_fit_multiple_model 
   ---------------------------------
    
   (1 row)
   ```
   
   
   3.214 | training in iteration 1
   3.243 | training in iteration 2
   3.232 | training in iteration 3
   3.338 | training in iteration 4
   3.147 | training in iteration 5
   1.034 | evaluating training dataset in iteration 5
   
   17.21 | total
    
   18.89 | E2E run time
    
   1.681 | other overhead time
   
   
   
   
   


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