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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