kaknikhil commented on a change in pull request #397: DL: Update content of
the model summary table
URL: https://github.com/apache/madlib/pull/397#discussion_r288223462
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File path: src/ports/postgres/modules/deep_learning/madlib_keras.py_in
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@@ -238,19 +223,22 @@ def fit(schema_madlib, source_table,
model,model_arch_table,
independent_varname_in_source_table =
src_summary_dict['independent_varname_in_source_table']
# Define some constants to be inserted into the summary table.
model_type = "madlib_keras"
- model_size = sys.getsizeof(model)
+ compile_params_dict = convert_string_of_args_to_dict(compile_params)
+ metrics_list = get_metrics_from_compile_param(compile_params)
+ is_metrics_specified = True if metrics_list else False
+ metrics_type = 'ARRAY{0}'.format(metrics_list) if is_metrics_specified
else 'NULL'
metrics_iters = metrics_iters if metrics_iters else 'NULL'
# We always compute the training loss and metrics, at least once.
- training_metrics_final = training_metrics[-1]
training_loss_final = training_loss[-1]
- training_metrics = training_metrics if training_metrics else 'NULL'
- training_loss = training_loss if training_loss else 'NULL'
+ training_loss = 'ARRAY{0}'.format(training_loss) if training_loss else
'NULL'
Review comment:
can't we avoid this if check if we use plpy prepare for training_loss and
others ?
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