kaknikhil commented on a change in pull request #393: DL: Add support for
reporting various metrics in fit/evaluate
URL: https://github.com/apache/madlib/pull/393#discussion_r285697353
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File path: src/ports/postgres/modules/deep_learning/madlib_keras.py_in
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@@ -282,30 +270,30 @@ def fit(schema_madlib, source_table,
model,model_arch_table,
$MAD${dependent_varname_in_source_table}$MAD$::TEXT AS
dependent_varname,
$MAD${independent_varname_in_source_table}$MAD$::TEXT AS
independent_varname,
$MAD${model_arch_table}$MAD$::TEXT AS model_arch_table,
- {model_arch_id} AS model_arch_id,
+ {model_arch_id}::INTEGER AS model_arch_id,
$1 AS compile_params,
$2 AS fit_params,
- {num_iterations} AS num_iterations,
+ {num_iterations}::INTEGER AS num_iterations,
{validation_table}::TEXT AS validation_table,
- {metrics_compute_frequency} AS metrics_compute_frequency,
+ {metrics_compute_frequency}::INTEGER AS metrics_compute_frequency,
$3 AS name,
$4 AS description,
'{model_type}'::TEXT AS model_type,
- {model_size} AS model_size,
+ {model_size}::INTEGER AS model_size,
'{start_training_time}'::TIMESTAMP AS start_training_time,
'{end_training_time}'::TIMESTAMP AS end_training_time,
$5 AS time_iter,
'{version}'::TEXT AS madlib_version,
- {num_classes} AS num_classes,
+ {num_classes}::INTEGER AS num_classes,
Review comment:
why do we need to typecast this one and the others to integer ? Aren't they
integer by default ?
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