orhankislal commented on a change in pull request #524:
URL: https://github.com/apache/madlib/pull/524#discussion_r583608832
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File path: src/ports/postgres/modules/deep_learning/madlib_keras_wrapper.py_in
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@@ -287,27 +298,50 @@ def parse_optimizer(compile_dict):
# Parse the fit parameters into a dictionary.
-def parse_and_validate_fit_params(fit_param_str):
+def parse_and_validate_fit_params(fit_param_str, current_seg_id=0):
if fit_param_str:
- fit_params_dict = convert_string_of_args_to_dict(fit_param_str)
-
- literal_eval_fit_params = ['batch_size','epochs','verbose',
+ fit_params_dict = convert_string_of_args_to_dict(fit_param_str,
strip_quotes=False)
+ literal_eval_fit_params = ['batch_size','epochs','verbose', 'shuffle',
'class_weight','initial_epoch','steps_per_epoch']
- accepted_fit_params = literal_eval_fit_params + ['shuffle']
+ accepted_fit_params = literal_eval_fit_params + ['callbacks']
fit_params_dict = validate_and_literal_eval_keys(fit_params_dict,
literal_eval_fit_params,
accepted_fit_params)
- if 'shuffle' in fit_params_dict:
- shuffle_value = fit_params_dict['shuffle']
- if shuffle_value == 'True' or shuffle_value == 'False':
- fit_params_dict['shuffle'] = bool(shuffle_value)
+
+ if 'callbacks' in fit_params_dict:
+ fit_params_dict['callbacks'] =
parse_callbacks(fit_params_dict['callbacks'], current_seg_id)
return fit_params_dict
else:
return {}
+# Parse the callback fit params and create the TensorBoard object in the
dictionary
+def parse_callbacks(callbacks, current_seg_id=0):
Review comment:
Even if we mock the database calls (is_superuser, etc.), we still need
the TensorBoard initializer. AFAIK, we haven't imported or mocked tf functions
in our unit tests but we can definitely try.
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