fmcquillan99 commented on pull request #518:
URL: https://github.com/apache/madlib/pull/518#issuecomment-698612856
output tables
```
madlib=# select * from automl_cifar10_output_summary;
-[ RECORD 1 ]-------------+-----------------------------------------
source_table | cifar10_train_packed
validation_table | cifar10_val_packed
model | automl_cifar10_output
model_info | automl_cifar10_output_info
dependent_varname | y
independent_varname | x
model_arch_table | model_arch_library
model_selection_table | automl_cifar10_mst_table
automl_method | hyperopt
automl_params | num_models=4, num_iters=2, algorithm=tpe
random_state | None
object_table | None
use_gpus | f
metrics_compute_frequency | 1
name | None
description | None
start_training_time | 2020-09-24 21:27:43
end_training_time | 2020-09-24 21:57:21
madlib_version | 1.18.0-dev
num_classes | 10
class_values | {0,1,2,3,4,5,6,7,8,9}
dependent_vartype | text
normalizing_const | 256
```
and
```
madlib=# select * from automl_cifar10_output_info;
-[ RECORD 1
]------------+-----------------------------------------------------------------------------------------------------------------------
mst_key | 1
model_id | 1
compile_params |
optimizer='SGD(lr=1.0060862144391352,momentum=2.477852193264555)',metrics=['accuracy'],loss='categorical_crossentropy'
fit_params | epochs=1,batch_size=128
model_type | madlib_keras
model_size | 4886.20019531
metrics_elapsed_time | {854.796041965485,1740.91218686104}
metrics_type | {accuracy}
loss_type | categorical_crossentropy
training_metrics_final | 0.100000001490116
training_loss_final | NaN
training_metrics | {0.100000001490116,0.100000001490116}
training_loss | {NaN,NaN}
validation_metrics_final | 0.100000001490116
validation_loss_final | NaN
validation_metrics | {0.100000001490116,0.100000001490116}
validation_loss | {NaN,NaN}
-[ RECORD 2
]------------+-----------------------------------------------------------------------------------------------------------------------
mst_key | 3
model_id | 2
compile_params |
optimizer='SGD(lr=1.0019632479006402,momentum=2.468115689403145)',metrics=['accuracy'],loss='categorical_crossentropy'
fit_params | epochs=1,batch_size=128
model_type | madlib_keras
model_size | 2159.70019531
metrics_elapsed_time | {867.580676794052,1753.89660692215}
metrics_type | {accuracy}
loss_type | categorical_crossentropy
training_metrics_final | 0.100000001490116
training_loss_final | NaN
training_metrics | {0.100000001490116,0.100000001490116}
training_loss | {NaN,NaN}
validation_metrics_final | 0.100000001490116
validation_loss_final | NaN
validation_metrics | {0.100000001490116,0.100000001490116}
validation_loss | {NaN,NaN}
-[ RECORD 3
]------------+-----------------------------------------------------------------------------------------------------------------------
mst_key | 4
model_id | 2
compile_params |
optimizer='Adam(lr=1.009549897036113)',metrics=['accuracy'],loss='categorical_crossentropy'
fit_params | epochs=1,batch_size=64
model_type | madlib_keras
model_size | 2159.70019531
metrics_elapsed_time | {880.187488794327,1766.73845982552}
metrics_type | {accuracy}
loss_type | categorical_crossentropy
training_metrics_final | 0.0999400019645691
training_loss_final | 14.5072526931763
training_metrics | {0.0996000021696091,0.0999400019645691}
training_loss | {14.5127325057983,14.5072526931763}
validation_metrics_final | 0.100100003182888
validation_loss_final | 14.5046730041504
validation_metrics | {0.101099997758865,0.100100003182888}
validation_loss | {14.4885559082031,14.5046730041504}
-[ RECORD 4
]------------+-----------------------------------------------------------------------------------------------------------------------
mst_key | 2
model_id | 1
compile_params |
optimizer='SGD(lr=1.0039632314582876,momentum=2.466481495072043)',metrics=['accuracy'],loss='categorical_crossentropy'
fit_params | epochs=1,batch_size=64
model_type | madlib_keras
model_size | 4886.20019531
metrics_elapsed_time | {885.122605800629,1772.07805681229}
metrics_type | {accuracy}
loss_type | categorical_crossentropy
training_metrics_final | 0.100000001490116
training_loss_final | NaN
training_metrics | {0.100000001490116,0.100000001490116}
training_loss | {NaN,NaN}
validation_metrics_final | 0.100000001490116
validation_loss_final | NaN
validation_metrics | {0.100000001490116,0.100000001490116}
validation_loss | {NaN,NaN}
```
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